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Frasheri, Mirgita. "Collaborative Adaptive Autonomous Agents." Licentiate thesis, Mälardalens högskola, Inbyggda system, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-40255.
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Grey, Stuart. "Distributed agents for autonomous spacecraft." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/3830/.
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Space missions have evolved considerably in the last fifty years in both complexity and ambition. In order to enable this continued improvement in the scientific and commercial return of space missions new control systems are needed that can manage complex combinations of state of the art hardware with a minimum of human interaction. Distributed multi-agent systems are one approach to controlling complex multisatellite space missions. A distributed system is not enough on its own however,the spacecraft must be able to carry out complex tasks such as planning,negotiation and close proximity formation flying autonomously. It is the coupling of distributed control with autonomy that is the focus of this thesis. Three contributions to the state of the art are described herein. They all involve the innovative use of multi-agent systems in space missions. The first is the development of a multi-agent architecture, HASA, specifically for space missions. The second is to use embedded agents to autonomously control an interferometric type space telescope. The third is based on software agents that coordinate multiple Earth observation missions coupled with a global optimisation technique for data extraction. The HASA architecture was developed in reaction to the over generality of most multi-agent architectures in the computer science and robotics literature and the ad-hoc, case-by-case approach, to multi-agent architectures when developed and deployed for space missions. The HASA architecture has a recursive nature which allows for the multi-agent system to be completely described throughout its development process as the design evolves and more sub-systems are implemented. It also inherits a focus on the robust generation of a product and safe operation from architectures in use in the manufacturing industry. A multi-agent system was designed using the HASA architecture for an interferometric space telescope type mission. This type of mission puts high requirements on formation flying and cooperation between agents. The formation flying agents were then implemented using a Java framework and tested on a multi-platform distributed simulation suite developed especially for this thesis. Three different control methods were incorporated into the agents and the multi-agent system was shown to be able to acquire and change formation and avoid collisions autonomously. A second multi-agent system was designed for the GMES mission in collaboration with GMV, the industrial partner in this project. This basic MAS design was transferred to the HASA architecture. A novel image selection algorithm was developed to work alongside the GMES multi-agent system. This algorithm uses global optimisation techniques to suggest image parameters to users based on the output of the multi-agent system.
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Allen, Stephen Richard. "Concern processing in autonomous agents." Thesis, University of Birmingham, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369169.
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Griffiths, Nathan. "Motivated cooperation in autonomous agents." Thesis, University of Warwick, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365266.
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DaBose, Michael W. "Autonomous agents for digital network maximization." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1997. http://handle.dtic.mil/100.2/ADA337729.
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Thesis (M.S. in Software Engineering)--Naval Postgraduate School, Sept. 1997.Thesis advisors: Luqi ; Berzins, Valdis. "September 1997." Includes bibliographical references (p. 108-112). Also Available online.
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Karnan, Sathia Murthy. "Knowledge based communication in autonomous agents." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ56334.pdf.
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Kaptan, Varol. "MODELING AUTONOMOUS AGENTS IN MILITARY SIMULATIONS." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3825.
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Simulation is an important tool for prediction and assessment of the behavior of complex systems and situations. The importance of simulation has increased tremendously during the last few decades, mainly because the rapid pace of development in the field of electronics has turned the computer from a costly and obscure piece of equipment to a cheap ubiquitous tool which is now an integral part of our daily lives. While such technological improvements make it easier to analyze well-understood deterministic systems, increase in speed and storage capacity alone are not enough when simulating situations where human beings and their behavior are an integral part of the system being studied. The problem with simulation of intelligent entities is that intelligence is still not well understood and it seems that the field of Artificial Intelligence (AI) has a long way to go before we get computers to think like humans. Behavior-based agent modeling has been proposed in mid-80's as one of the alternatives to the classical AI approach. While used mainly for the control of specialized robotic vehicles with very specific sensory capabilities and limited intelligence, we believe that a behavior-based approach to modeling generic autonomous agents in complex environments can provide promising results. To this end, we are investigating a behavior-based model for controlling groups of collaborating and competing agents in a geographic terrain. In this thesis, we are focusing on scenarios of military nature, where agents can move within the environment and adversaries can eliminate each other through use of weapons. Different aspects of agent behavior like navigation to a goal or staying in group formation, are implemented by distinct behavior modules and the final observed behavior for each agent is an emergent property of the combination of simple behaviors and their interaction with the environment. Our experiments show that while such an approach is quite efficient in terms of computational power, it has some major drawbacks. One of the problems is that reactive behavior-based navigation algorithms are not well suited for environments with complex mobility constraints where they tend to perform much worse than proper path planning. This problem represents an important research question, especially when it is considered that most of the modern military conflicts and operations occur in urban environments. One of the contributions of this thesis is a novel approach to reactive navigation where goals and terrain information are fused based on the idea of transforming a terrain with obstacles into a virtual obstacle-free terrain. Experimental results show that our approach can successfully combine the low run-time computational complexity of reactive methods with the high success rates of classical path planning. Another interesting research problem is how to deal with the unpredictable nature of emergent behavior. It is not uncommon to have situations where an outcome diverges significantly from the intended behavior of the agents due to highly complex nonlinear interactions with other agents or the environment itself. Chances of devising a formal way to predict and avoid such abnormalities are slim at best, mostly because such complex systems tend to be be chaotic in nature. Instead, we focus on detection of deviations through tracking group behavior which is a key component of the total situation awareness capability required by modern technology-oriented and network-centric warfare. We have designed a simple and efficient clustering algorithm for tracking of groups of agent suitable for both spatial and behavioral domain. We also show how to detect certain events of interest based on a temporal analysis of the evolution of discovered clusters.Ph.D.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Computer Science
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Szarowicz, Adam. "Artificial intelligence for animated autonomous agents." Thesis, Kingston University, 2004. http://eprints.kingston.ac.uk/20735/.
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Automatic creation of animated crowd scenes involving multiple interacting characters is currently a field of extensive research. This is because automatic generation of animation finds immediate applications in film post-production and special effects, computer games or event simulation in crowded areas. The work presented here addresses the problem of inadequate application of AI techniques in current animation research. The thesis presents a survey of different industrial and academic approaches and a number of lacking features are identified. After extensive research in existing systems an agent-based system and an animation framework are chosen for extension and the cognitive architecture FreeWill is proposed. The architecture further extends its underlying principles and combines software agent solutions with typical animation elements. It also allows for easy integration with existing tools. Another important contribution of FreeWill is a proposal of an algorithm for automatic generation of high-level actions using reinforcement learning. The chosen learning technique lends itself well to the animation task, as reinforcement learning allows for easy definition of the learning task - only the ultimate goal of the learning agent must be defined. The process of defining and conducting the learning task is explained in detail. The learning module allows for further automation of the process of animation generation, shortens the task of creating crowd scenes and also reduces the production costs. Newly learnt actions can be applied to increase the quality of the generated sequences. The learning module can be used in both deterministic and non-deterministic environments. Experiments in both modes are presented, and conclusions are drawn. Two modes of control - inverse and forward kinematics are also compared and a number of experiments are demonstrated. Learning with inverse kinematics control was found to converge faster for the same task. A working prototype of the architecture is presented and the learnt motion is compared with human motion. The results of the comparison demonstrate that the learning scheme could be used to imitate human motion in crowd scenes. Finally a number of metrics are defined which allow for easy selection of most relevant actions from the learnt set, again helping to automate the process. The work concludes with pointing out further directions of research based on this work and suggests possible extensions and applications.
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Coddington, Alexandra Margrit. "Self motivated planning in autonomous agents." Thesis, University College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.249232.
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Vorrath, Jonathan J. "Implementing METOC transformation : applying autonomous agents /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Sep%5FVorrath.pdf.
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Abel, Ryan Orlin. "The coordinated control of autonomous agents." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/772.
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This thesis considers the coordinated control of autonomous agents. The agents are modeled as double integrators, one for each Cartesian dimension. The goal is to force the agents to converge to a formation specified by their desired relative positions. To this end a pair of one-step-ahead optimization based control laws are developed.
The control algorithms produce a communication topology that mirrors the geometric formation topology due to the careful choice of the minimized cost functions. Through this equivalence a natural understanding of the relationship between the geometric formation topology and the communication infrastructure is gained. It is shown that the control laws are stable and guarantee convergence for all viable formation topologies. Additionally, velocity constraints can be added to allow the formation to follow fixed or arbitrary time dependent velocities.
Both control algorithms only require local information exchange. As additional agents attach to the formation, only those agents that share position constraints with the joining agents need to adjust their control laws. When redundancy is incorporated into the formation topology, it is possible for the system to survive loss of agents or communication channels. In the event that an agent drops out of the formation, only the agents with position interdependence on the lost agent need to adjust their control laws. Finally, if a communication channel is lost, only the agents that share that communication channel must adjust their control laws.
The first control law falls into the category of distributed control, since it requires either the global information exchange to compute the formation size or an a priori knowledge of the largest possible formation. The algorithm uses the network size to penalize the control input for each formation. When using a priori knowledge, it is shown that additional redundancy not only adds robustness to loss of agents or communication channels, but it also decreases the settling times to the desired formation. Conversely, the overall control strategy suffers from sluggish response when the network is small with respect to the largest possible network. If global information exchange is used, scalability suffers.
The second control law was developed to address the negative aspects of the first. It is a fully decentralized controller, as it does not require global information exchange or any a priori knowledge.
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Zrehen, Stéphane. "Elements of brain design for autonomous agents /." [S.l.] : [s.n.], 1995. http://library.epfl.ch/theses/?nr=1373.
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Hearne, John Henry. "NPSNET : physically based, autonomous, naval surface agents /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA273231.
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Hearne, John H. "NPSNET: physically based, autonomous, naval surface agents." Thesis, Monterey, California. Naval Postgraduate School, 1993. http://hdl.handle.net/10945/39950.
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Approved for public release; distribution is unlimited.The Computer Science Department at the Naval Postgraduate School in Monterey, California has developed a low-cost real-time interactive simulation system using the Distributed Interactive Simulation (DIS) Protocol, known as NPSNET, that works on commercia
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Downs, Joseph. "An investigation into architectures for autonomous agents." Thesis, University of Nottingham, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240299.
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Faratin, Peyman. "Automated service negotiation between autonomous computational agents." Thesis, Queen Mary, University of London, 2000. http://qmro.qmul.ac.uk/xmlui/handle/123456789/28945.
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Multi-agent systems are a new computational approach for solving real world, dynamic and open system problems. Problems are conceptualized as a collection of decentralised autonomous agents that collaborate to reach the overall solution. Because of the agents autonomy, their limited rationality, and the distributed nature of most real world problems, the key issue in multi-agent system research is how to model interactions between agents. Negotiation models have emerged as suitable candidates to solve this interaction problem due to their decentralised nature, emphasis on mutual selection of an action, and the prevalence of negotiation in real social systems. The central problem addressed in this thesis is the design and engineering of a negotiation model for autonomous agents for sharing tasks and/or resources. To solve this problem a negotiation protocol and a set of deliberation mechanisms are presented which together coordinate the actions of a multiple agent system. In more detail, the negotiation protocol constrains the action selection problem solving of the agents through the use of normative rules of interaction. These rules temporally order, according to the agents' roles, communication utterances by specifying both who can say what, as well as when. Specifically, the presented protocol is a repeated, sequential model where offers are iteratively exchanged. Under this protocol, agents are assumed to be fully committed to their utterances and utterances are private between the two agents. The protocol is distributed, symmetric, supports bi and/or multi-agent negotiation as well as distributive and integrative negotiation. In addition to coordinating the agent interactions through normative rules, a set of mechanisms are presented that coordinate the deliberation process of the agents during the ongoing negotiation. Whereas the protocol normatively describes the orderings of actions, the mechanisms describe the possible set of agent strategies in using the protocol. These strategies are captured by a negotiation architecture that is composed of responsive and deliberative decision mechanisms. Decision making with the former mechanism is based on a linear combination of simple functions called tactics, which manipulate the utility of deals. The latter mechanisms are subdivided into trade-off and issue manipulation mechanisms. The trade-off mechanism generates offers that manipulate the value, rather than the overall utility, of the offer. The issue manipulation mechanism aims to increase the likelihood of an agreement by adding and removing issues into the negotiation set. When taken together, these mechanisms represent a continuum of possible decision making capabilities: ranging from behaviours that exhibit greater awareness of environmental resources and less to solution quality, to behaviours that attempt to acquire a given solution quality independently of the resource consumption. The protocol and mechanisms are empirically evaluated and have been applied to real world task distribution problems in the domains of business process management and telecommunication management. The main contribution and novelty of this research are: i) a domain independent computational model of negotiation that agents can use to support a wide variety of decision making strategies, ii) an empirical evaluation of the negotiation model for a given agent architecture in a number of different negotiation environments, and iii) the application of the developed model to a number of target domains. An increased strategy set is needed because the developed protocol is less restrictive and less constrained than the traditional ones, thus supporting development of strategic interaction models that belong more to open systems. Furthermore, because of the combination of the large number of environmental possibilities and the size of the set of possible strategies, the model has been empirically investigated to evaluate the success of strategies in different environments. These experiments have facilitated the development of general guidelines that can be used by designers interested in developing strategic negotiating agents. The developed model is grounded from the requirement considerations from both the business process management and telecommunication application domains. It has also been successfully applied to five other real world scenarios.
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He, Minghua. "Designing bidding strategies for autonomous trading agents." Thesis, University of Southampton, 2004. https://eprints.soton.ac.uk/259999/.
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Increasingly many systems are being conceptualised, designed and implemented as marketplaces in which autonomous software entities (agents) trade services. These services can be commodities in e-commerce applications or data and knowledge services in information economies. In such systems, dynamic pricing through some form of negotiation or auction protocol is becoming the norm for many goods and customers. Thus, negotiation capabilities for software agents are a central concern. Specifically, agents need to be able to prepare bids for and evaluate offers on behalf of the parties they represent with the aim of obtaining the maximum benefit for their users. They do this according to some negotiation strategies. However, in many cases, determining which strategy to employ is a complex decision making task because of the inherent uncertainty and dynamics of the situation. To this end, this thesis is concerned with developing bidding strategies for a range of auction contexts. In this thesis, we focus on a number of agent mediated e-commerce settings. In particular, we design novel strategies for the continuous double auctions, for the international trading agent competition that involves multiple interrelated auctions, and for multiple overlapping English auctions. All these strategies have been empirically benchmarked against the main other models that have been proposed in the literature and, in all cases, our strategies have been shown to be superior in a wide range of circumstances. Moreover all our models exploit soft computing methods, in particular fuzzy logic and neuro-fuzzy techniques. Such methods are used to cope with the significant degrees of uncertainty that exist in on-line auctions and we show they are a practical solution method for this class of applications. In developing such strategies we believe this work represents an important step towards realising the full potential of bidding agents in e-commerce scenarios.
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Giansiracusa, Michelangelo Antonio. "A secure infrastructural strategy for safe autonomous mobile agents." Thesis, Queensland University of Technology, 2005. https://eprints.qut.edu.au/16052/1/Michaelangelo_Giansiracusa_Thesis.pdf.
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Portable languages and distributed paradigms have driven a wave of new applications and processing models. One of the most promising, certainly from its early marketing, but disappointing (from its limited uptake)is the mobile agent execution and data processing model. Mobile agents are autonomous programs which can move around a heterogeneous network such as the Internet, crossing through a number of different security domains, and perform some work at each visited destination as partial completion of a mission for their agent user.
Despite their promise as a technology and paradigm to drive global electronic services (i.e.any Internet-driven-and-delivered service, not solely e-commerce related activities), their up take on the Internet has been very limited. Chief among the reasons for the paradigm's practical under-achievement is there is no ubiquitous frame work for using Internet mobile agents, and non-trivial security concerns abound for the two major stake holders (mobile agent users and mobile agent platform owners).
While both stake holders have security concerns with the dangers of the mobile agent processing model, most investigators in the field are of the opinion that protecting mobile agents from malicious agent platforms is more problematic than protecting agent platforms from malicious mobile agents. Traditional cryptographic mechanisms are not well-suited to counter the bulk of the threats associated with the mobile agent paradigm due to the untrusted hosting of an agent and its intended autonomous, flexible movement and processing.
In our investigation, we identified that the large majority of the research undertaken on mobile agent security to date has taken a micro-level perspective. By this we mean research focused solely on either of the two major stakeholders, and even then often only on improving measures to address one security issue dear to the stake holder - for example mobile agent privacy (for agent users) or access control to platform resources (for mobile agent platform owners).
We decided to take a more encompassing, higher-level approach in tackling mobile agent security issues. In this endeavour, we developed the beginnings of an infrastructural-approach to not only reduce the security concerns of both major stakeholders, but bring them transparently to a working relationship. Strategic utilisation of both existing distributed system trusted-third parties (TTPs) and novel mobile agent paradigm-specific TTPs are fundamental in the infrastructural framework we have devised.
Besides designing an application and language independent frame work for supporting a large-scale Internet mobile agent network, our Mobile Agent Secure Hub Infrastructure (MASHIn) proposal encompasses support for flexible access control to agent platform resources. A reliable means to track the location and processing times of autonomous Internet mobile agents is discussed, withfault-tolerant handling support to work around unexpected processing delays. Secure,highly-effective (incomparison to existing mechanisms) strategies for providing mobile agent privacy, execution integrity, and stake holder confidence scores were devised - all which fit comfortably within the MASHIn framework. We have deliberately considered the interests - withoutbias -of both stake holders when designing our solutions.
In relation to mobile agent execution integrity, we devised a new criteria for assessing the robustness of existing execution integrity schemes. Whilst none of the existing schemes analysed met a large number of our desired properties for a robust scheme, we identified that the objectives of Hohl's reference states scheme were most admirable - particularly real - time in - mission execution integrity checking. Subsequently, we revised Hohl's reference states protocols to fit in the MASHIn framework, and were able to overcome not only the two major limitations identified in his scheme, but also meet all of our desired properties for a robust execution integrity scheme (given an acceptable decrease in processing effiency).
The MASHIn offers a promising new perspective for future mobile agent security research and indeed a new frame work for enabling safe and autonomous Internet mobile agents. Just as an economy cannot thrive without diligent care given to micro and macro-level issues, we do not see the security prospects of mobile agents (and ultimately the prospects of the mobile agent paradigm) advancing without diligent research on both levels.
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Giansiracusa, Michelangelo Antonio. "A Secure Infrastructural Strategy for Safe Autonomous Mobile Agents." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16052/.
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Portable languages and distributed paradigms have driven a wave of new applications and processing models. One of the most promising, certainly from its early marketing, but disappointing (from its limited uptake)is the mobile agent execution and data processing model. Mobile agents are autonomous programs which can move around a heterogeneous network such as the Internet, crossing through a number of different security domains, and perform some work at each visited destination as partial completion of a mission for their agent user. Despite their promise as a technology and paradigm to drive global electronic services (i.e.any Internet-driven-and-delivered service, not solely e-commerce related activities), their up take on the Internet has been very limited. Chief among the reasons for the paradigm's practical under-achievement is there is no ubiquitous frame work for using Internet mobile agents, and non-trivial security concerns abound for the two major stake holders (mobile agent users and mobile agent platform owners). While both stake holders have security concerns with the dangers of the mobile agent processing model, most investigators in the field are of the opinion that protecting mobile agents from malicious agent platforms is more problematic than protecting agent platforms from malicious mobile agents. Traditional cryptographic mechanisms are not well-suited to counter the bulk of the threats associated with the mobile agent paradigm due to the untrusted hosting of an agent and its intended autonomous, flexible movement and processing. In our investigation, we identified that the large majority of the research undertaken on mobile agent security to date has taken a micro-level perspective. By this we mean research focused solely on either of the two major stakeholders, and even then often only on improving measures to address one security issue dear to the stake holder - for example mobile agent privacy (for agent users) or access control to platform resources (for mobile agent platform owners). We decided to take a more encompassing, higher-level approach in tackling mobile agent security issues. In this endeavour, we developed the beginnings of an infrastructural-approach to not only reduce the security concerns of both major stakeholders, but bring them transparently to a working relationship. Strategic utilisation of both existing distributed system trusted-third parties (TTPs) and novel mobile agent paradigm-specific TTPs are fundamental in the infrastructural framework we have devised. Besides designing an application and language independent frame work for supporting a large-scale Internet mobile agent network, our Mobile Agent Secure Hub Infrastructure (MASHIn) proposal encompasses support for flexible access control to agent platform resources. A reliable means to track the location and processing times of autonomous Internet mobile agents is discussed, withfault-tolerant handling support to work around unexpected processing delays. Secure,highly-effective (incomparison to existing mechanisms) strategies for providing mobile agent privacy, execution integrity, and stake holder confidence scores were devised - all which fit comfortably within the MASHIn framework. We have deliberately considered the interests - withoutbias -of both stake holders when designing our solutions. In relation to mobile agent execution integrity, we devised a new criteria for assessing the robustness of existing execution integrity schemes. Whilst none of the existing schemes analysed met a large number of our desired properties for a robust scheme, we identified that the objectives of Hohl's reference states scheme were most admirable - particularly real - time in - mission execution integrity checking. Subsequently, we revised Hohl's reference states protocols to fit in the MASHIn framework, and were able to overcome not only the two major limitations identified in his scheme, but also meet all of our desired properties for a robust execution integrity scheme (given an acceptable decrease in processing effiency). The MASHIn offers a promising new perspective for future mobile agent security research and indeed a new frame work for enabling safe and autonomous Internet mobile agents. Just as an economy cannot thrive without diligent care given to micro and macro-level issues, we do not see the security prospects of mobile agents (and ultimately the prospects of the mobile agent paradigm) advancing without diligent research on both levels.
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Verame, Jhim Kiel M. "Helping users adopt and delegate agency to autonomous agents in everyday life." Thesis, University of Southampton, 2018. https://eprints.soton.ac.uk/423558/.
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Autonomous agents are designed to take actions on behalf of users, acting autonomously upon data from sensors or online sources. However, the performance and actions of such agents are liable to uncertainties. As such, the design of interaction mechanisms that enable users to understand the operation of autonomous agents and flexibly delegate or regain control is an open challenge for HCI. Against this background, in this thesis we report on three studies designed to better understand how to help users interact with autonomous agents. In particular, we begin by understanding how people deal with uncertainties when delegating agency to autonomous services. We then examined the impact of different agent-designs and feedback mechanisms, inspired by the factors that encourages people to delegate agency in an everyday setting. Based on our findings, we discuss key implications for the design of future autonomous technologies and the design of interaction mechanisms to help users make the best use of such systems.
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La, Boissonniere François. "An approach to design autonomous agents within ModSAF." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/Mq44911.pdf.
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Hartley, Thomas Peter. "Online adaptation for autonomous agents in interactive environments." Thesis, University of Wolverhampton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.508867.
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Korsavva, Sofia. "High-availability autonomous clusters : an intelligent agents approach." Thesis, University of Sheffield, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.401178.
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Saunders, Eric S. "Optimal observing ofastronomical time series using autonomous agents." Thesis, University of Exeter, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445453.
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NETO, BALDOINO FONSECA DOS SANTOS. "A DEONTIC APPROACH TO DEVELOP AUTONOMOUS NORMATIVE AGENTS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19639@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICONormas sociais têm se tornado uma das abordagens mais promissoras para garantir uma ordem social desejável em sistemas multiagentes. Nestes sistemas, agentes autônomos trabalham a fim de atingir objetivos comuns ou diferentes. Normas regulam o comportamento de tais agentes definindo obrigações e proibições, fornecendo recompensas e estabelecendo punições a fim de incentivá-los a se comportarem de acordo com as normas. Embora o uso de normas seja um mecanismo promissor para regular o comportamento de agentes, o desenvolvimento de agentes capazes de atuar em um sistema, adotar as normas e lidar com as mesmas autonomamente tem sido mais difícil do que o desenvolvimento de agentes tradicionais. A razão para esta dificuldade é a falta de mecanismos que possibilitem o desenvolvimento de agentes autônomos capazes de lidar com questões relacionadas a normas. Nesta tese, apresenta-se uma abordagem para desenvolvimento de agentes capazes de lidar autonomamente com questões normativas. Para tanto, a abordagem fornece um modelo arquitetural para apoiar um agente no raciocínio sobre as normas. Tal modelo estende o modelo Belief-Desire-Intention adicionando um conjunto de funções que auxiliam o agente na adoção de novas normas, na verificação da ativação, desativação, cumprimento e violação das normas, na seleção de quais normas devem ser cumpridas ou violadas, na detecção e resolução de conflitos entre normas, na geração de novos objetivos e na seleção de objetivos, planos e intenções, levando em consideração as normas do sistema. Além disto, a abordagem fornece os mecanismos necessários para implementação de agentes projetados a partir do modelo arquitetural proposto. Dois cenários são utilizados para exemplificar a abordagem proposta. O primeiro está relacionado ao planejamento de missões de resgate reguladas por normas. O segundo está relacionado ao suporte ao desenvolvimento de software regulado por normas. Por fim, experimentos são apresentados que demonstram a importância de desenvolver agentes a partir da abordagem proposta seja na visão do agente ou da sociedade.
Social norms have become one of the most promising approaches toward ensuring a desirable social outcome in multi-agent systems. In these systems, autonomous and heterogeneous agents work toward common or different goals. Norms regulate the behaviour of these agents by defining obligations and prohibitions, and by creating rewards and penalties to encourage the agents to behave so as to meet these norms. Although the use of norms is a promising mechanism to regulate the agents’ behavior, the development of agents able to join an agents society, to adopt the norms and to work with them autonomously has shown to be significantly more challenging than traditional agents. The reason for this difficulty is the lack of agent models that allow developing of autonomous agents able to cope with issues related to norms. In this thesis, we introduce an approach to develop agents able to deal with normative questions in an autonomous way. The approach extends the Belief-Desire- Intention model including functions that assist the agent in adopting new norms, in verifying norm activation, deactivation, fulfillment and violation, in selecting the norms to be fulfilled or violated by the agent, in identifying and overcoming conflicts among norms, in generating new goals from norms and in selecting goals, plans and intentions while taking into account the system norms. In addition, the approach provides mechanisms that are necessary to implement agents designed from the proposed architectural model. Two scenarios are used in order to exemplify the proposed approach. The first is related to the planning of rescue missions regulated by norms. The second is related to the support to software development regulated by norms. Finally, experiments that demonstrate the importance of developing agent by using the proposed architectural model, both in the agent and society point of view, are presented.
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Charlish, A. B. "Autonomous agents for multi-function radar resource management." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1334115/.
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The multifunction radar, aided by advances in electronically steered phased array technology, is capable of supporting numerous, differing and potentially conflicting tasks. However, the full potential of the radar system is only realised through its ability to automatically manage and configure the finite resource it has available. This thesis details the novel application of agent systems to this multifunction radar resource management problem. Agent systems are computational societies where the synergy of local interactions between agents produces emergent, global desirable behaviour. In this thesis the measures and models which can be used to allocate radar resource is explored; this choice of objective function is crucial as it determines which attribute is allocated resource and consequently constitutes a description of the problem to be solved. A variety of task specific and information theoretic measures are derived and compared. It is shown that by utilising as wide a variety of measures and models as possible the radar’s multifunction capability is enhanced. An agent based radar resource manager is developed using the JADE Framework which is used to apply the sequential first price auction and continuous double auctions to the multifunction radar resource management problem. The application of the sequential first price auction leads to the development of the Sequential First Price Auction Resource Management algorithm from which numerous novel conclusions on radar resource management algorithm design are drawn. The application of the continuous double auction leads to the development of the Continuous Double Auction Parameter Selection (CDAPS) algorithm. The CDAPS algorithm improves the current state of the art by producing an improved allocation with low computational burden. The algorithm is shown to give worthwhile improvements in task performance over a conventional rule based approach for the tracking and surveillance functions as well as exhibiting graceful degradation and adaptation to a dynamic environment.
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Meshref, Hossam. "Modeling Autonomous Agents' Behavior Using Neuro-Immune Networks." Diss., Virginia Tech, 2002. http://hdl.handle.net/10919/28473.
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Autonomous robots are expected to interact with their dynamic changing environment. This interactions requires certain level of behavior based Intelligence, which facilitates the dynamic adaptation of the robot behavior accordingly with his surrounding environment. Many researches have been done in biological information processing systems to model the behavior of an autonomous robot. The Artificial Immune System (AIS) provides new paradigm suitable for dynamic problem dealing with unknown environment rather than a static problem. The immune system has some features such as memory, tolerance, diversity and more features that can be used in engineering applications.
The immune system has an important feature called meta-dynamics in which new species of antibodies are produced continuously from the bone marrow. If the B-Cell (robot) cannot deal with the current situation, new behaviors (antibodies) should be generated by the meta dynamics function. This behavior should be incorporated into the existing immune system to gain immunity against new environmental changes. We decided to use a feed forward Artificial Neural Network (ANN) to simulate this problem, and to build the AIS memory.
Many researchers have tried to tackle different points in mimicking the biological immune system, but no one previously has proposed such an acquired memory. This contribution is made as a "proof of concept" to the field of biological immune system simulation as a start of further research efforts in this direction. Many applications can potentially use our designed Neuro-Immune Network (NIN), especially in the area of autonomous robotics. We demonstrated the use of the designed NIN to control a robot arm in an unknown environment. As the system encounters new cases, it will increase its ability to deal with old and new situations encountered. This novel technique can be applied to many robotics applications in industry, where autonomous robots are required to have adaptive behavior in response to their environmental changes. Regarding future work, the use of VLSI neural networks to enhance the speed of the system for real time applications can be investigated along with possible methods of design and implementation of a similar VLSI chip for the AIN.Ph. D.
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Lecerf, Ugo. "Robust learning for autonomous agents in stochastic environments." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS253.
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Nous explorons une approche par l'apprentissage par renforcement (RL) pour qu'un agent autonome soit robuste aux risques et incertitudes rencontrés dans une tâche de navigation. Nous étudions les effets des changements soudains des conditions de leur environnement sur des agents autonomes et explorons des méthodes qui permettent à un agent de correctement réagir aux imprévus de son environnement pour lesquelles il n'a pas été explicitement formé. Inspiré par le circuit de dopamine humain, la performance d'un agent RL est mesurée et optimisée en termes de récompenses et de pénalités qu'il reçoit pour un comportement désirable ou indésirable. Notre approche initiale consiste à apprendre à estimer la distribution des récompenses attendues de l'agent, et à utiliser les informations sur les modes de cette distribution pour obtenir des informations nuancées sur la façon dont un agent peut agir dans une situation à haut risque. Nous montrons également que nous sommes capables d'apprendre une stratégie robuste aux incertitudes de l'environnement en apprenant les stratégies de contingence les plus efficaces, où la complexité informatique de la tâche d'apprentissage est partagée entre plusieurs agents. Nous combinons ensuite cette approche avec un module de planification hiérarchique qui est utilisé pour planifier efficacement les différents agents de telle sorte que l'ensemble des agents soit capable de réagir aux changements imprévus de l'environnement. Cela nous permet d'adhérer à des contraintes plus strictes et plus explicites qui peuvent être mises en œuvre et mesurées au moyen d'un planificateur hiérarchiqueIn this work we explore data-driven deep reinforcement learning (RL) approaches for an autonomous agent to be robust to a navigation task, and act correctly in the face of risk and uncertainty. We investigate the effects that sudden changes to environment conditions have on autonomous agents and explore methods which allow an agent to have a high degree of generalization to unforeseen, sudden modifications to its environment it was not explicitly trained to handle. Inspired by the human dopamine circuit, the performance of an RL agent is measured and optimized in terms of rewards and penalties it receives for desirable or undesirable behaviour. Our initial approach is to learn to estimate the distribution of expected rewards from the agent, and use information about modes in this distribution to gain nuanced information about how an agent can act in a high-risk situation. Later, we show that we are able to achieve the same robustness objective with respect to uncertainties in the environment by attempting to learn the most effective contingency policies in a `divide and conquer' approach, where the computational complexity of the learning task is shared between multiple policy models. We then combine this approach with a hierarchical planning module which is used to effectively schedule the different policy models in such a way that the collection of contingency plans is able to be highly robust to unanticipated environment changes. This combination of learning and planning enables us to make the most of the adaptability of deep learning models, as well as the stricter and more explicit constraints that can be implemented and measured by means of a hierarchical planner
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Santamaria, Juan Carlos. "Learning adaptive reactive agents." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/9247.
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Bulos, Remedios de dios. "Goal formulation in intelligence agents." Thesis, University of Sussex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285077.
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The development of the research "Goal Formulation in Intelligent Agents" is anchored on the rationale that to be truly called "intelligent", an agent must not only be capable of knowing how to achieve its given goals; preferably, it must also have the capability to formulate its own goals. It must be able to detect its own goals, assess their feasibility, prioritize them, evaluate their validity as to whether they have to be acted upon, terminated, or suspended. This research has developed and implemented an intelligent system that is capable for formulating its own goals. Goal formulation refers to the intelligent behavior that an agent exhibits when reasoning about what goals to pursue and when to pursue them. It is an integrated reasoning mechanism that identifies the relevant goals that an agent needs to accomplish to affect the external world (Goal detection); constantly updates the qualitative and quantitative information attributed to the active goals as events unfold (Active goal status evaluation); assesses whether a goal is attainable through the application of the agent's own actions (Goal achievability assessment); and dynamically evaluates the relative merits of an agent's tasks, provides the agent with a sound basis to make a rational choice among a set of competing alternatives and then decides what to do next based on the choice made (Next action selection). In the development of the goal formulator, the types and structure of the required knowledge are identified; architectures for the various goal formulation components have been designed; and algorithms for the various goal formulation reasoning mechanisms (e.g. application of NPV economic decision criterion) have been developed and implemented in Prolog. To prove the applicability of the goal formulation concepts that this research had developed, the system was applied in the housekeeping domain. Simulations of some housekeeping cases are provided.
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Suro, François. "Epigenetic learning of autonomous behaviours in a society of agents." Thesis, Montpellier, 2020. http://www.theses.fr/2020MONTS049.
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Les humains et les robots sont des agents autonomes qui agissent dans les limites du monde physique. Cependant, l'intelligence et l'autonomie des humains est bien supérieure à celle des machines. Inspirée de la psychologie et des neurosciences, la robotique développementale vise à donner aux agents artificiels la capacité de s'adapter, d'apprendre et de se développer de manière autonome, afin d'atteindre, voire de surpasser les capacités humaines. De nombreux domaines sont impliqués dans la recherche de meilleures méthodes d'apprentissage sensorimoteur, de systèmes de mémoire, de représentations émergentes de symboles et de langages, de systèmes de motivation, ainsi que le développement de nombreuses stratégies d'apprentissage allant de l'exploration à l'imitation et à l'apprentissage social.Cependant, la majorité de ces recherches se concentrent sur un aspect particulier. Très peu d'entre elles s'attaquent au problème de l'intelligence incarnée dans son ensemble, du développement initial à l'interaction avec d'autres agents intelligents. Il existe donc un réel besoin d'étudier quelles structures sous-jacentes peuvent unifier cette hétérogénéité des buts et des moyens techniques dans un système en perpétuelle évolution.Notre objectif est de fournir une telle structure, capable d'apprendre des compétences sensorimotrices ainsi que des compétences plus complexes allant au-delà du simple comportement réactif. La contribution majeure de cette thèse est une architecture hiérarchique, appelée MIND, utilisant une conception modulaire pour l'apprentissage cumulatif de compétences. Dans MIND, les informations sensorielles et les commandes de coordination entre les compétences sont traitées comme des signaux, en utilisant une approche connexionniste.À partir d'un travail préliminaire sur la spécialisation sociale, nous menons une série d'expériences utilisant MIND pour accumuler des comportements complexes basés sur des comportements sensorimoteurs simples. Nous intégrons ensuite des systèmes de mémoires pour apprendre des comportements sociaux reproduisant notre modèle initial de spécialisation sociale.Nous montrons la capacité de MIND à gérer l'hétérogénéité des comportements à apprendre et des systèmes à coordonner. L'utilisation d'une approche inspirée du connexionnisme, basée sur le signal, comme architecture sous-jacente a permis l'apprentissage à la fois de comportements sensorimoteurs et de décision, ainsi que l'émergence de représentations mémoires.Au-delà des avantages de MIND comme support pour la conception d'agents développementaux, notre travail montre la faisabilité du développement continu et les avantages de l'incarnation dans l'ancrage du comportement émergent, ce qui soutient le point de vue de la robotique développementale comme approche pour une IA généralisteHumans and robots are autonomous agents acting within the constraints of the physical world. However, the intelligence and autonomy of humans is far superior to that of machines. Inspired by psychology and neurosciences, developmental robotics aims to give artificial agents the ability to adapt, learn and develop autonomously, in order to reach or even exceed the capabilities of humans. Many research fields are involved in the improvement of sensorimotor skill training, memory systems, emergent representations of symbols and languages, motivational systems, and the development of many learning strategies ranging from exploration to imitation and social learning.However, most of these research projects are focused on a very specific and limited task. Few of them aim to bring together all aspects of embodied intelligence, from the initial development of behaviours to the interactions with other intelligent agents. There is therefore a real need to study which underlying structures can unify this heterogeneity of goals and methods in a perpetually evolving system.Our goal is to provide such a structure, capable of learning sensorimotor skills as well as more complex skills that go beyond simple reactive behaviour. The main contribution of this thesis is a hierarchical architecture using modular properties to achieve cumulative skill learning, namely MIND. In MIND, sensory information and coordination commands between skills are both treated as signals, using a connectionist inspired approach.Starting from preliminary work on social specialization in multi-agent systems, we conduct a series of experiments using a MIND hierarchy to accumulate behaviours, from simple sensorimotor behaviours to social behaviours. We first build complex behaviours based on simple reactive behaviours, then integrate simple memory systems with complex behaviours, and finally use these memory systems to learn social behaviours that replicate our initial model of social specialization.We show that such an architecture is capable of managing the heterogeneity of the behaviours to be learned and the systems to be coordinated. The use of a connectionist approach, a signal-based system, as the underlying architecture made learning both motor control and decision behaviour possible, and also lead to the emergence of memory representations.Beyond the benefits of MIND as a support for designing developmental agents, our work shows the feasibility of continuous development and the advantages of embodiment in grounding the emergent behaviour, which supports developmental robotics as an approach to general purpose AI
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Gloor, Christian. "Modelling of autonomous agents in a realistic road network." Zürich : ETH, Eidgenössische Technische Hochschule Zürich, Dept. für Informatik, 2001. http://e-collection.ethbib.ethz.ch/show?type=dipl&nr=44.
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Jarne, Ornia Daniel. "Ant Colony Algorithms andits applications to Autonomous Agents Systems." Thesis, KTH, Optimeringslära och systemteori, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217391.
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With the latest advancements in autonomous agents systems and technology, there is a growing interest in developing control algorithms and methods to coordinate large numbers of robotic entities. Following this line of work, the use of biologically inspired algorithms based on swarm emerging behaviour presents some really interesting properties for controlling multiple agents. They rely on very simple instructions and communications to develop a coordinated structure in the system. Particularly, this master thesis focuses on the study of Ant Colony algorithms based on stigmergy interaction to coordinate agents and perform a certain task. The first part focuses on the theoretical background and algorithm convergence proof, while the second part consists of experimental simulations and results. For this, some metric parameters have been developed and found to be especially useful in the study of a simple path planning test case. The main concept developed in this work is an adaptation of Shannon Entropy that measures uniformity and order in the system and the weighted graph. This parameter has been used to study the performance and results of an autonomous agent system based on Ant Colony algorithms. Finally, this control algorithm has been modified to develop an event-triggered control scheme. Using the properties of the weighted graph (Entropy) and the sensing of the agents, a decentralized event-triggered method has been implemented and tested, and has been found to increase efficiency in the usage of system resources.Med den senaste tidens utveckling inom autonoma agentsystem och teknologier, finns ett ökat intresse för utveckling av styralgoritmer och metoder för att koordinera stora mängder robotenheter. Inom detta område visar användandet av biologiskt inspirerade algoritmer, baserade på naturliga svärmbeteenden, intressanta egenskaper som kan utnyttjas i styrandet av system som innefattar ett flertal agenter. Dessa är uppbyggda av simpla instruktioner och kommunikationsmedel för att tillgodose struktur i systemet. I synnerhet fokuserar detta masterexamensarbete på studier av Ant Colony-algoritmer, baserade på stigmergy-interaktion för att koordinera enheter och få dem att utföra specifika uppgifter. Den första delen behandlar den teoretiska bakgrunden och konvergensbevis medan den andra delen i huvudsak består av experimentella simuleringar samt resultat. Till detta ändamål har metriska parametrar utvecklats, vilka ansågs särskilt användbara när planeringen av en enkel bana studerades. Huvudkonceptet som utvecklats i detta arbete är en tillämpning av Shannon- Entropi, vilket mäter enhetlighet och ordning i ett system samt den viktade grafen. Denna parameter har använts för att studera prestandan och resultaten hos ett autonomt agentsystem baserat på Ant Colony-algoritmer. Slutligen har denna styralgoritm modifierats för att utveckla ett händelsestyrt styrschema. Genom att använda egenskaperna hos den viktade grafen (entropi) tillsammans med sensorsystemet hos agentenheterna, så har en decentraliserad händelsestyrd metod implementerats, testats och visat sig ge ökad effektivitet gällande utnyttjandet av systemresurser.
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Jaafar, Jafreezal. "Reactive behaviour for autonomous virtual agents using fuzzy logic." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/8317.
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One of the fundamental aspects of a virtual environment is the virtual agents that inhabit them. In many applications, virtual agents are required to perceive input information from their environment and make decisions appropriate to their task based on their programmed reaction to those inputs. The research presented in this thesis focuses on the reactive behaviour of the agents. We propose a new control architecture to allow agents to behave autonomously in navigation tasks in unknown environments. Our behaviour-based architecture uses fuzzy logic to solve problems of agent control and action selection and which can coordinate conflicts among different operations of reactive behaviours. A Fuzzy Associative Memory (FAM) is used as the process of encoding and mapping the input fuzzy sets to the output fuzzy set and to optimise the fuzzy rules. Our action selection algorithm is based on the fuzzy α-level method with the Hurwicz criterion. The main objective of the thesis was to implement agent navigation from point to point by a coordination of planning, sensing and control. However, we believe that the reactive architecture emerging from this research is sufficiently general that it could be applied to many applications in widely differing domains where real-time decision making under uncertainty is required. To illustrate this generality, we show how the architecture is applied to a different domain. We chose the example of a computer game since it clearly demonstrates the attributes of our architecture: real-time action selection and handling uncertainty. Experimental results are presented for both implementations which show how the fuzzy method is applied, its generality and that it is robust enough to handle different uncertainties in different environments. In summary, the proposed reactive architecture is shown to solve aspects of behaviour control for autonomous virtual agents in virtual environments and can be applied to various application domains.
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Sommaruga, Lorenzo. "Cooperative heuristics for autonomous agents : an artificial intelligence perspective." Thesis, University of Nottingham, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335853.
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Marti, Stefan Johannes Walter 1965. "Autonomous interactive intermediaries : social intelligence for mobile communication agents." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/35523.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (p. 151-167).
Today's cellphones are passive communication portals. They are neither aware of our conversational settings, nor of the relationship between caller and callee, and often interrupt us at inappropriate times. This thesis is about adding elements of human style social intelligence to our mobile communication devices in order to make them more socially acceptable to both user and local others. I suggest the concept of an Autonomous Interactive Intermediary that assumes the role of an actively mediating party between caller, callee, and co-located people. In order to behave in a socially appropriate way, the Intermediary interrupts with non-verbal cues and attempts to harvest 'residual social intelligence' from the calling party, the called person, the people close by, and its current location. For example, the Intermediary obtains the user's conversational status from a decentralized network of autonomous body-worn sensor nodes. These nodes detect conversational groupings in real time, and provide the Intermediary with the user's conversation size and talk-to-listen ratio. The Intermediary can 'poll' all participants of a face-to-face conversation about the appropriateness of a possible interruption by slightly vibrating their wirelessly actuated finger rings.
(cont.) Although the alerted people do not know if it is their own cellphone that is about to interrupt, each of them can veto the interruption anonymously by touching his/her ring. If no one vetoes, the Intermediary may interrupt. A user study showed significantly more vetoes during a collaborative group-focused setting than during a less group oriented setting. The Intermediary is implemented as a both a conversational agent and an animatronic device. The animatronics is a small wireless robotic stuffed animal in the form of a squirrel, bunny, or parrot. The purpose of the embodiment is to employ intuitive non-verbal cues such as gaze and gestures to attract attention, instead of ringing or vibration. Evidence suggests that such subtle yet public alerting by animatronics evokes significantly different reactions than ordinary telephones and are seen as less invasive by others present when we receive phone calls. The Intermediary is also a dual conversational agent that can whisper and listen to the user, and converse with a caller, mediating between them in real time.
(cont.) The Intermediary modifies its conversational script depending on caller identity, caller and user choices, and the conversational status of the user. It interrupts and communicates with the user when it is socially appropriate, and may break down a synchronous phone call into chunks of voice instant messages.
by Stefan Johannes Walter Marti.
Ph.D.
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Whitten, Andrew (Andrew Koo). "Decentralized planning for autonomous agents cooperating in complex missions." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62490.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 121-125).
Planning for autonomous vehicles remains an important and challenging research topic. This thesis focuses on decentralized planning for autonomous agents performing complex missions. These types of missions often involve a set of tasks, each representing a component of the mission. Task planning algorithms may be used as part of the mission planner to assign agents to tasks; however, the decentralized task assignment problem becomes increasingly difficult when there exists coupling in the task set. Coupling may be in the form of assignment relationships, where the value of a task is condition on whether or not another task has been assigned, or temporal relationships where the value of a task is conditioned on when it is performed relative to other tasks. In this work, task coupling is treated as a constraint, and a task planning framework is introduced which is specifically designed to ensure that all coupled constraints are satisfied by the assignment. The new algorithm is developed from a baseline Consensus-Based Bundle Algorithm (CBBA) and is called Coupled- Constraint CBBA, or CCBBA. The new algorithm is compared to the baseline in a complex mission simulation and is found to outperform the baseline by up to a factor of 3 with respect to assignment score. A separate extension to CBBA is also developed for satisfying refuel constraints in the task assignment process, and the technique is verified through numerical simulation. Lastly, this thesis examines the autonomous search problem where a fleet of sensor-equipped agents are deployed to find objects of interest in an environment. A local search strategy developed for the Onboard Planning System for UAVs in Support of Expeditionary Reconnaissance and Surveillance (OPS-USERS) program is described, which is a receding horizon optimization technique. A global search strategy is also described which extends the planning horizon of the local search strategy by incorporating larger amounts of information into the planning. The two strategies are compared both with and without an artificially simulated human operator, and the global search strategy is shown to outperform the local search strategy in terms of number of targets found.
by Andrew Whitten.
S.M.
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AL-Buraiki, Omar S. M. "Specialized Agents Task Allocation in Autonomous Multi-Robot Systems." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41504.
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With the promise to shape the future of industry, multi-agent robotic technologies have the potential to change many aspects of daily life. Over the coming decade, they are expected to impact transportation systems, military applications such as reconnaissance and surveillance, search-and-rescue operations, or space missions, as well as provide support to emergency first responders.
Motivated by the latest developments in the field of robotics, this thesis contributes to the evolution of the future generation of multi-agent robotic systems as they become smarter, more accurate, and diversified in terms of applications. But in order to achieve these goals, the individual agents forming cooperative robotic systems need to be specialized in what they can accomplish, while ensuring accuracy and preserving the ability to perform diverse tasks.
This thesis addresses the problem of task allocation in swarm robotics in the specific context where specialized capabilities of the individual agents are considered. Based on the assumption that each individual agent possesses specialized functional capabilities and that the expected tasks, which are distributed in the surrounding environment, impose specific requirements, the proposed task allocation mechanisms are formulated in two different spaces. First, a rudimentary form of the team members’ specialization is formulated as a cooperative control problem embedded in the agents’ dynamics control space. Second, an advanced formulation of agents’ specialization is defined to estimate the individual agents’ task allocation probabilities in a dedicated specialization space, which represents the core contribution of this thesis to the advancement and practice in the area of swarm robotics.
The original task allocation process formulated in the specialization space evolves through four stages of development. First, a task features recognition stage is conceptually introduced to leverage the output of a sensing layer embedded in robotic agents to drive the proposed task allocation scheme. Second, a matching scheme is developed to best match each agent’s specialized capabilities with the corresponding detected tasks. At this stage, a general binary definition of agents’ specialization serves as the basis for task-agent association. Third, the task-agent matching scheme is expanded to an innovative probabilistic specialty-based task-agent allocation framework to generalize the concept and exploit the potential of agents’ specialization consideration. Fourth, the general framework is further refined with a modulated definition of the agents’ specialization based on their mechanical, physical structure, and embedded resources. The original framework is extended and a prioritization layer is also introduced to improve the system’s response to complex tasks that are characterized based on the recognition of multiple classes.
Experimental validation of the proposed specialty-based task allocation approach is conducted in simulation and on real-world experiments, and the results are presented and discussed in light of potential applications to demonstrate the effectiveness and efficiency of the proposed framework.
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Hess, Traci J. "A Study of Autonomous Agents in Decision Support Systems." Diss., Virginia Tech, 1998. http://hdl.handle.net/10919/11277.
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Software agents have been heralded as the most important emerging technology of the decade. As software development firms eagerly attempt to integrate these autonomous programs into their products, researchers attempt to define the concept of agency and to develop architectures that will improve agent capabilities. Decision Support System (DSS) researchers have been eager to integrate agents into their applications, and exploratory works in which agents have been used within a DSS have been documented. This dissertation attempts to further this exploration by studying the agent features and underlying architectures that can lead to the successful integration of agents in DSS.
This exploration is carried out in three parts. In the first part, a review of the relevant research streams is provided. The history and current status of software agents is first discussed. Similarly, a historical and current view of DSS research is provided. Lastly, a historical and tutorial-type of discussion is provided on the topic of Artificial Intelligence (AI) planning. This review of the relevant literature provides a general background for the conceptual analyses and implementations that are carried out in the next two sections.
In the second part, the literature on software agents is synthesized to develop a definition of agency applicable to DSS. Using this definition, an agent-integrated DSS that supports variance-analysis is designed and developed. Following this implementation, a general framework for agent-enabling DSS is suggested. The use of this framework promises to raise some DSS to a new level of capability whereby "what-if" systems are transformed into real-time, proactive systems.
The third part utilizes this general framework to agent-enable a corporate-planning system DSS and extends the framework in the second section through the introduction of an automated-planning agent. The agent uses AI planning to generate decision-making alternatives, providing a means to integrate and sequence the models in the DSS. The architecture used to support this planning agent is described. This new kind of DSS enables not only the monitoring of goals, but also the maintenance of these goals through agent-generated plans.
The conclusion summarizes the contributions of this work and outlines in considerable detail potential research opportunities in the realm of software agents, DSS, and planning.Ph. D.
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Karakurt, Murat Özdemir Serhan. "Data driven modeling using reinforcement learning in autonomous agents/." [s.l.]: [s.n.], 2003. http://library.iyte.edu.tr/tezler/master/makinamuh/T000276.pdf.
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Michael, Andrew Mario. "Circle formation algorithm for autonomous agents with local sensing /." Online version of thesis, 2004. http://hdl.handle.net/1850/12143.
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Nyussupov, Adlet. "Using Autonomous Agents for Software Testing Based on JADE." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-45319.
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The thesis work describes the development of a multiagent testing application (MTA) based on an agent approach for solving challenges in regression testing domain, such as: reducing the complexity of testing, optimizing the time consumption, increasing the efficiency and implementing the automation of this approach for regression testing. All these challenges related to effectiveness and cost, can be represented as measures of achieved code coverage and number of test cases created. A multiagent approach is proposed in this thesis since it allows the implementation of the autonomous behaviour and optimizes the data processing in a heterogeneous environment. In addition, the agent-based approach provides flexible design methods for building multitask applications and conducting parallel task execution. However, all of these advantages of using an agent-based approach need to be investigated in the regression testing domain for realistic scenarios. Therefore, a hypothesis was formulated in order to investigate the efficiency of the MTA approach using an experiment as the main research method for obtaining results. The thesis includes a comparison analysis between the MTA and well-known test case generation tools (i.e. EvoSuite and JUnitTools) for identifying the differences in terms of efficiency and code coverage achieved. The comparison results showed advantages of the MTA within regression testing context due to optimal level of code coverage and test cases. The outcome of the thesis work moves toward solving the aforementioned problems in regression testing domain and shows some advantages of using the multagent approach within regression testing context.
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Chen, Xingping. "Robust nonlinear trailing control for multiple mobile autonomous agents formation." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1155591282.
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LoÌpez, y. LoÌpez Fabiola. "Social power and norms : impact on agent behaviour." Thesis, University of Southampton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273756.
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Williams, Stephen Vincent. "Visual arctic navigation: techniques for autonomous agents in glacial environments." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41135.
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Arctic regions are thought to be more sensitive to climate change fluctuations, making weather data from these regions more valuable for climate modeling. Scientists have expressed an interest in deploying a robotic sensor network in these areas, minimizing the exposure of human researchers to the harsh environment, while allowing dense, targeted data collection to commence. For any such robotic system to be successful, a certain set of base navigational functionality must be developed. Further, these navigational algorithms must rely on the types of low-cost sensors that would be viable for use in a multi-agent system. A set of vision-based processing techniques have been proposed, which augment current robotic technologies for use in glacial terrains. Specifically, algorithms for estimating terrain traversability, robot localization, and terrain reconstruction have been developed which use data collected exclusively from a single camera and other low-cost robotic sensors. For traversability assessment, a custom algorithm was developed that uses local scale surface texture to estimate the terrain slope. Additionally, a horizon line estimation system has been proposed that is capable of coping with low-contrast, ambiguous horizons. For localization, a monocular simultaneous localization and mapping (SLAM) filter has been fused with consumer-grade GPS measurements to produce full robot pose estimates that do not drift over long traverses. Finally, a terrain reconstruction methodology has been proposed that uses a Gaussian process framework to incorporate sparse SLAM landmarks with dense slope estimates to produce a single, consistent terrain model. These algorithms have been tested within a custom glacial terrain computer simulation and against multiple data sets acquired during glacial field trials. The results of these tests indicate that vision is a viable sensing modality for autonomous glacial robotics, despite the obvious challenges presented by low-contrast glacial scenery. The findings of this work are discussed within the context of the larger arctic sensor network project, and a direction for future work is recommended.
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Bermudez, Contreras Edgar. "Modelling active bio-inspired object recognition in autonomous mobile agents." Thesis, University of Sussex, 2010. http://sro.sussex.ac.uk/id/eprint/2364/.
Full textAbstract:
Object recognition is arguably one of the main tasks carried out by the visual cortex. This task has been studied for decades and is one of the main topics being investigated in the computer vision field. While vertebrates perform this task with exceptional reliability and in very short amounts of time, the visual processes involved are still not completely understood. Considering the desirable properties of the visual systems in nature, many models have been proposed to not only match their performance in object recognition tasks, but also to study and understand the object recognition processes in the brain. One important point most of the classical models have failed to consider when modelling object recognition is the fact that all the visual systems in nature are active. Active object recognition opens different perspectives in contrast with the classical isolated way of modelling neural processes such as the exploitation of the body to aid the perceptual processes. Biologically inspired models are a good alternative to study embodied object recognition since animals are a working example that demonstrates that object recognition can be performed with great efficiency in an active manner. In this thesis I study biologically inspired models for object recognition from an active perspective. I demonstrate that by considering the problem of object recognition from this perspective, the computational complexity present in some of the classical models of object recognition can be reduced. In particular, chapter 3 compares a simple V1-like model (RBF model) with a complex hierarchical model (HMAX model) under certain conditions which make the RBF model perform as the HMAX model when using a simple attentional mechanism. Additionally, I compare the RBF and HMAX model with some other visual systems using well-known object libraries. This comparison demonstrates that the performance of the implementations of the RBF and HMAX models employed in this thesis is similar to the performance of other state-of-the-art visual systems. In chapter 4, I study the role of sensors in the neural dynamics of controllers and the behaviour of simulated agents. I also show how to employ an Evolutionary Robotics approach to study autonomous mobile agents performing visually guided tasks. In addition, in chapter 5 I investigate whether the variation in the visual information, which is determined by simple movements of an agent, can impact the performance of the RBF and HMAX models. In chapter 6 I investigate the impact of several movement strategies in the recognition performance of the models. In particular I study the impact of the variation in visual information using different movement strategies to collect training views. In addition, I show that temporal information can be exploited to improve the object recognition performance using movement strategies. In chapter 7 experiments to study the exploitation of movement and temporal information are carried out in a real world scenario using a robot. These experiments validate the results obtained in simulations in the previous chapters. Finally, in chapter 8 I show that by exploiting regularities in the visual input imposed by movement in the selection of training views, the complexity of the RBF model can be reduced in a real robot. The approach of this work proposes to gradually increase the complexity of the processes involved in active object recognition, from studying the role of moving the focus of attention while comparing object recognition models in static tasks, to analysing the exploitation of an active approach in the selection of training views for a object recognition task in a real world robot.
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Johnson, Michael Boyle. "Build-a-dude : action selection networks for computational autonomous agents." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/67395.
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Undurti, Aditya. "Planning under uncertainty and constraints for teams of autonomous agents." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68405.
Full textAbstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 155-164).
One of the main advantages of unmanned, autonomous vehicles is their potential use in dangerous situations, such as victim search and rescue in the aftermath of an urban disaster. Unmanned vehicles can complement human first responders by performing tasks that do not require human expertise (e.g., communication) and supplement them by providing capabilities a human first responder would not have immediately available (e.g., aerial surveillance). However, for unmanned vehicles to work seamlessly and unintrusively with human responders, a high degree of autonomy and planning is necessary. In particular, the unmanned vehicles should be able to account for the dynamic nature of their operating environment, the uncertain nature of their tasks and outcomes, and the risks that are inherent in working in such a situation. This thesis therefore addresses the problem of planning under uncertainty in the presence of risk. This work formulates the planning problem as a Markov Decision Process with constraints, and offers a formal definition for the notion of "risk". Then, a fast and computationally efficient solution is proposed. Next, the complications that arise when planning for large teams of unmanned vehicles are considered, and a decentralized approach is investigated and shown to be efficient under some assumptions. However some of these assumptions place restrictions - specifically on the amount of risk each agent can take. These restrictions hamper individual agents' ability to adapt to a changing environment. Hence a consensus-based approach that allows agents to take more risk is introduced and shown to be effective in achieving high reward. Finally, some experimental results are presented that validate the performance of the solution techniques proposed.
by Aditya Undurti.
Ph.D.
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Chen, Xingpeng. "Robust nonlinear trailing control for multiple mobile autonomous agents formation." The Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1155591282.
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Ingram, Dennis J. "Autonomous agents for distributed intrusion detection in a multi-host environment." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA369795.
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