Relevant bibliographies by topics / Agents

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Agents'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Agents"

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Islabão Franco, Márcia Häfele, Antônio Carlos Da Rocha Costa, and Helder Coelho. "EXCHANGE VALUES AND SOCIAL POWER SUPPORTING THE CHOICE OF PARTNERS." Revista Pueblos y fronteras digital 5, no. 9 (June 1, 2010): 43. http://dx.doi.org/10.22201/cimsur.18704115e.2010.9.159.

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In this paper, we adopt Piaget’s theory of social exchanges, in which an interaction is an exchange of services between agents, such that agents assign subjective, qualitative values —called exchange values— to the actions and objects they exchange during interactions. The agents present characteristics related to social power during the interactions. In this paper, we show how these characteristics are considered in the agents’ reasoning. This paper also shows how these characteristics and the exchange values can influence the agents’ choice of future partners, in support of groupformation. RESUMENEn el presente trabajo adoptamos la teoría piagetiana de los intercambios sociales, donde una interacción es un intercambio de servicios entre agentes, de tal manera que dichos agentes asignan valores subjetivos, cualitativos —denominados valores de intercambio— a las acciones y objetos que intercambian en la interacción. Durante las interacciones los agentes presentan características relativas al poder social. En este trabajo mostramos cómo los agentes consideran dichas características en su razonamiento. Asimismo, el texto muestra cómo estas características y los valores de intercambio pueden influir sobre la futura elección de asociados del agente para la formación de grupo.
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Elijah and Muhammad Naveed Dilber. "Complete Analysis of Fault Tolerance Schemes in Mobile Agents for a Reliable Mobile Agent Computation." Bonfring International Journal of Industrial Engineering and Management Science 7, no. 1 (March 31, 2017): 20–24. http://dx.doi.org/10.9756/bijiems.8322.

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Steinberg, Leigh. "Agents and Agency: a Sports Agent's View." Journal of Sport and Social Issues 16, no. 2 (September 1992): 113–15. http://dx.doi.org/10.1177/019372359201600205.

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Sengupta, Raja, and Renée Sieber. "Geospatial Agents, Agents Everywhere . . ." Transactions in GIS 11, no. 4 (July 27, 2007): 483–506. http://dx.doi.org/10.1111/j.1467-9671.2007.01057.x.

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Eissa, A. M. F. "Amphoteric surface active agents." Grasas y Aceites 46, no. 4-5 (October 30, 1995): 240–44. http://dx.doi.org/10.3989/gya.1995.v46.i4-5.931.

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Kumar Katta, Prashanth. "Composition of Bonding Agents." Indian Journal of Dental Education 13, no. 2 (April 1, 2020): 75–77. http://dx.doi.org/10.21088/ijde.0974.6099.13220.5.

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Saini, Akash, and Pritee Gupta. "CHRONOTHERAPEUTIC AGENTS: AN OVERVIEW." INDIAN RESEARCH JOURNAL OF PHARMACY AND SCIENCE 4, no. 3 (September 2017): 1144–52. http://dx.doi.org/10.21276/irjps.2017.4.3.8.

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Simone, Joseph V. "Are We Single Agents, Double Agents, or Free Agents?" Oncology Times 26, no. 8 (April 2004): 3–4. http://dx.doi.org/10.1097/01.cot.0000291847.72455.35.

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Zrari, Chadha, Hela Hachicha, and Khaled Ghedira. "Agent's Security During Communication in Mobile Agents System." Procedia Computer Science 60 (2015): 17–26. http://dx.doi.org/10.1016/j.procs.2015.08.100.

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Wang, Na, Zhihai Rong, and Wen Yang. "Opinion dynamics of improved Hegselmann-Krause model with agent's stubbornness and stubborn agents." Europhysics Letters 143, no. 5 (September 1, 2023): 52001. http://dx.doi.org/10.1209/0295-5075/acf39a.

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Abstract In this work, we improve the Hegselmann-Krause model (HK model) by combining the agent's stubbornness and the quantitative impact of stubborn agents on the evolution of other agents’ opinions. We divide stubborn agents into expert stubborn agents, environmentally stubborn agents and intrinsically stubborn agents based on the impact weight and agent's characteristics. We simulate the evolution of opinions of the improved HK model, and find that it is closer to reality. We also study the impact of the influence coefficient and the proportion of intrinsically stubborn agents on the stabilization time, and find that the presence of non-expert stubborn agents reduces the rate of convergence of opinions. Finally, we verify the effectiveness of the improved HK model by two real social events.
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Dissertations / Theses on the topic "Agents"

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Lau, Pik Lik Billy. "Interdependence between agents in multi agent systems." Thesis, Curtin University, 2014. http://hdl.handle.net/20.500.11937/439.

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Interdependence relationships have defined the foundation of cooperation between agents but limited by existing protocols. As a consequence, the idle agents are not able to join and benefit through it. First, the inter-relationship has been studied and certified for the purpose of securing mutual gains. Next, the join coalition mechanism is proposed to help idle agents to join existing macroscopic and microscopic coalitions which are based on the goals compatibilities, budget and trust
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Dinu, Razvan. "Web Agents : towards online hybrid multi-agent systems." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20126/document.

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Multi-agent systems have been used in a wide range of applications from computer-based simulations and mobile robots to agent-oriented programming and intelligent systems in real environments. However, the largest environment in which software agents can interact is, without any doubt, the World Wide Web and ever since its birth agents have been used in various applications such as search engines, e-commerce, and most recently the semantic web. However, agents have yet to be used on the Web in a way that leverages the full power of artificial intelligence and multi-agent systems, which have the potential of making life much easier for humans. This thesis investigates how this can be changed, and how agents can be brought to the core of the online experience in the sense that we want people to talk and interact with agents instead of "just using yet another application or website". We analyze what makes it hard to develop intelligent agents on the web and we propose a web agent model (WAM) inspired by recent results in multi-agent systems. Nowadays, a simple conceptual model is the key for widespread adoption of new technologies and this is why we have chosen the MASQ meta-model as the basis for our approach, which provides the best compromise in terms of simplicity of concepts, generality and applicability to the web. Since until now the model was introduced only in an informal way, we also provide a clear formalization of the MASQ meta-model.Next, we identify the three main challenges that need to be addressed when building web agents: integration of bodies, web semantics and user friendliness. We focus our attention on the first two and we propose a set of principles to guide the development of what we call strong web agents. Finally, we validate our proposal through the implementation of an award winning platform called Kleenk. Our work is just a step towards fulfilling the vision of having intelligent web agents mediate the interaction with the increasingly complex World Wide Web
Multi-agent systems have been used in a wide range of applications from computer-based simulations and mobile robots to agent-oriented programming and intelligent systems in real environments. However, the largest environment in which software agents can interact is, without any doubt, the World Wide Web and ever since its birth agents have been used in various applications such as search engines, e-commerce, and most recently the semantic web. However, agents have yet to be used on the Web in a way that leverages the full power of artificial intelligence and multi-agent systems, which have the potential of making life much easier for humans. This thesis investigates how this can be changed, and how agents can be brought to the core of the online experience in the sense that we want people to talk and interact with agents instead of "just using yet another application or website". We analyze what makes it hard to develop intelligent agents on the web and we propose a web agent model (WAM) inspired by recent results in multi-agent systems. Nowadays, a simple conceptual model is the key for widespread adoption of new technologies and this is why we have chosen the MASQ meta-model as the basis for our approach, which provides the best compromise in terms of simplicity of concepts, generality and applicability to the web. Since until now the model was introduced only in an informal way, we also provide a clear formalization of the MASQ meta-model.Next, we identify the three main challenges that need to be addressed when building web agents: integration of bodies, web semantics and user friendliness. We focus our attention on the first two and we propose a set of principles to guide the development of what we call strong web agents. Finally, we validate our proposal through the implementation of an award winning platform called Kleenk. Our work is just a step towards fulfilling the vision of having intelligent web agents mediate the interaction with the increasingly complex World Wide Web
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Doskočilová, Veronika. "Využití agentů v business procesech." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124783.

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This work deals with the possibilities of using agents and multiagent systems in the areas of business process management and business process modeling. The aim of the theoretical part is to describe the theory of artificial agents, to assess the benefits of this approach and to describe current applications of MAS in BPM. In the theoretical part I also describe the issue of management and business process modeling and methodology MMABP. The aim of the analytical part is to summarize the possibilities of using MAS in BPM in the situations where business processes are already described and modeled and in the situations where there are no such descripctions nor models yet . In this part I also want to introduce my theory of agent-process, which is the possibility of looking at processes as autonomous agents. This theory is presented in practical demonstrations and examples by using the TROPOS methodology, and this theory is supported by references from the areas of agent and business process modeling.
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Harder, Malte. "Information driven self-organization of agents and agent collectives." Thesis, University of Hertfordshire, 2014. http://hdl.handle.net/2299/13907.

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From a visual standpoint it is often easy to point out whether a system is considered to be self-organizing or not, though a quantitative approach would be more helpful. Information theory, as introduced by Shannon, provides the right tools not only quantify self-organization, but also to investigate it in relation to the information processing performed by individual agents within a collective. This thesis sets out to introduce methods to quantify spatial self-organization in collective systems in the continuous domain as a means to investigate morphogenetic processes. In biology, morphogenesis denotes the development of shapes and form, for example embryos, organs or limbs. Here, I will introduce methods to quantitatively investigate shape formation in stochastic particle systems. In living organisms, self-organization, like the development of an embryo, is a guided process, predetermined by the genetic code, but executed in an autonomous decentralized fashion. Information is processed by the individual agents (e.g. cells) engaged in this process. Hence, information theory can be deployed to study such processes and connect self-organization and information processing. The existing concepts of observer based self-organization and relevant information will be used to devise a framework for the investigation of guided spatial self-organization. Furthermore, local information transfer plays an important role for processes of self-organization. In this context, the concept of synergy has been getting a lot attention lately. Synergy is a formalization of the idea that for some systems the whole is more than the sum of its parts and it is assumed that it plays an important role in self-organization, learning and decision making processes. In this thesis, a novel measure of synergy will be introduced, that addresses some of the theoretical problems that earlier approaches posed.
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Vanzan, Alessio <1993&gt. "Mobile Agents Rendezvous in Networks Despite a Malicious Agent." Master's Degree Thesis, Università Ca' Foscari Venezia, 2017. http://hdl.handle.net/10579/10604.

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The use of mobile agents, i.e., autonomous software entities , finds its application in many settings such as Network Maintenance, Electronic commerce and Intelligent search. Given a network, we have a set of mobile agents that moves from node to node in order to achieve a common task. Security is an important issue that can arise in such environment and that has been widely studied in literature. In particular, it is important to study the problem of having a host or an agent that hinders or harms the honest agents in their tasks. In this thesis we consider a scenario in which one of the mobile agents may behave maliciously and thus act in order to prevent the other agents to complete their goal. We study the Rendezvous problem,i.e., the problem of gathering a set of mobile agents at a single node of a network, starting from a initial scattered configuration and despite the presence of a Malicious agent, and in particular, we propose a novel solution in the bidirectional hypercube network.
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d'Inverno, Mark. "Agents, agency and autonomy : a formal computational model." Thesis, University College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.586863.

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In recent years, there has been an explosion of interest in agents and multi-agent systems in a variety of areas including artificial intelligence, and software engineering. Agent technology, however, is still relatively young, and there is much debate and discussion over many important concepts and the relevant terminology. In particular, in a great deal of agent research, agents themselves are defined in wildly different ways, if at all, and this makes it extremely difficult to be explicit about their nature and functionality. These problems have arisen in part due to the lack of a common structure and language for describing and reasoning about both single agents and multi-agent systems, which might facilitate a rigorous organisation of the field. In response to this, a four-tiered theoretical formal framework for agent systems is proposed, which we use as a base from which to develop a detailed model of agents and their dimensions, the properties required by agents for effective operation, and the social organisation of multi-agent systems. This framework essentially comprises entities, objects, agents and autonomous agents, and specifies the relationships between them to provide a rigorous and detailed analysis of the structures underlying all such systems. Key to the understanding of this work is our overarching concern as computer scientists, of building computational systems. The development of formal theories and systems as proposed above is inadequate if they are irrelevant to the needs of practitioners. While the construction of any theory or model is unavoidably somewhat removed from the realities of software development, we address this concern by ensuring that the tools used are standard software engineering ones that are accessible and support practical development. In illustration of these ideas, and as a demonstration of the validity of the arguments made, we show how the framework and models developed can both provide a theoretical foundation and be applied directly to existing agent systems and theories: in particular, the Contract Net Protocol, AgentS- peak(L) and Social Dependence Networks.
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Nagi, Khaled [Verfasser]. "Transactional agents : towards a robust multi-agent system / K. Nagi." Berlin, 2001. http://d-nb.info/965521001/34.

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Tajer, Jean. "Detection of malicious hosts against agents in Mobile Agent networks." Thesis, University of Portsmouth, 2018. https://researchportal.port.ac.uk/portal/en/theses/detection-of-malicious-hosts-against-agents-in-mobile-agent-networks(beca3871-a989-4137-9a4d-13c88d8893d9).html.

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Over the last decade, networks have become increasingly advanced in terms of size, complexity and the level of heterogeneity, due to increase of number of users, devices and implementation of cloud among big enterprises and developing smart cities. As networks become more complicated, the existing client-server paradigm suffers from problems such as delay, jitter, bad quality of service, insufficient scalability, availability and flexibility. The appearance of mobile agents' technology is getting popular as means for an efficient way to access remote resources on computer networks. Mobile Agent- systems usually benefit from the following: asynchronous execution, dynamic adaptation, fault-tolerance improvement in network latency, protocol encapsulation, reduction in network load and robustness. However, one of the major technical obstacles to a wider acceptance of the mobile agent is security which is the modus operandi to protect the mobile agents against malicious hosts. This work proposes how the Mobile Agents (MA), supported by a new solid models (detection and protection), can present a new way of securing mobile agents against malicious hosts. The work contributes in proposing a new computing model for protection against malicious hosts. This model is based on trust, which is a combination of two kinds of trust: policy enforcement and control and punishment. The originality of this model is the introduction of the concept of setting up an active storage element in the agent space, called as "home away from home", for partial result storage and separation as well as digital signing of the destination of the mobile agent. An efficient flooding detection scheme is developed by integrating the sketch technique with the Divergence Measures (Hellinger Distance, Chi-Square and Power Divergences). This type of integration can be considered unique in comparison with existing solutions over a Mobile Agent network. The sketch data- structure summarizes the mobile agent's process of calls generating into a fixed set of data for developing a probability model. The Divergence Measures techniques, combined with a Mobile Agent traffic, efficiently identifies attacks, by monitoring the distance between current traffic distribution and the estimated distribution, based on history information. Compared to the previous detection system and existing works, the proposed techniques achieve the advantages of higher accuracy and flexibility, to deal with low intensity attacks and the ability to track the period of attack. Simulation results are presented to demonstrate the performance of the proposed detection model. This work achieves in outperforming the existing detection solutions by tuning the Divergence Measures. An evaluation of the scheme is done via the receiver-operating characteristic (ROC). The work achieves in outperforming the existing detection solutions by tuning the Power Divergence with a value of β=2.2. With this value of β, the detection scheme leads to a very attractive performance in terms of True Positive Rate (100%), False Positive Rate (3.8%) and is capable of detecting low intensity attacks. Moreover, the Power Divergence with β=2.2 presents a better detection accuracy of 98.1% in comparison with Hellinger Distance (60%) and Chi-square (80%). Since the scenarios in consideration in this work can be reasonably related to any type of network, the strength of the proposed model can alternatively be applied to any enterprise network.
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Huerta, Jose Manuel. "Attitudes of county Extension agents toward agent specialization in Ohio /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487846354481973.

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Huerta, Jose M. "Attitudes of county extension agents toward agent specialization in Ohio." Connect to resource, 1993. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1202155098.

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Books on the topic "Agents"

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Alonso, Eduardo, Daniel Kudenko, and Dimitar Kazakov, eds. Adaptive Agents and Multi-Agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44826-8.

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Bui, The Duy, Tuong Vinh Ho, and Quang Thuy Ha, eds. Intelligent Agents and Multi-Agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89674-6.

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Kuwabara, Kazuhiro, and Jaeho Lee, eds. Intelligent Agents and Multi-Agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45680-5.

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Barley, Michael Wayne, and Nik Kasabov, eds. Intelligent Agents and Multi-Agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b107183.

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Kotz, David, and Friedemann Mattern, eds. Agent Systems, Mobile Agents, and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/b75241.

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Lee, Jaeho, and Mike Barley, eds. Intelligent Agents and Multi-Agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/b94219.

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Kinny, David, Jane Yung-jen Hsu, Guido Governatori, and Aditya K. Ghose, eds. Agents in Principle, Agents in Practice. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25044-6.

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Law Reform Commission of Victoria. Inquiry agents, guard agents and watchmen. Melbourne: The Commisssion, 1989.

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Cockayne, William R. Mobile agents. Greenwich, CT: Manning, 1998.

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Kudenko, Daniel, Dimitar Kazakov, and Eduardo Alonso, eds. Adaptive Agents and Multi-Agent Systems II. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b106974.

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Book chapters on the topic "Agents"

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Roberts, John. "Agency without Agents." In Belief and Organization, 144–62. London: Palgrave Macmillan UK, 2012. http://dx.doi.org/10.1057/9781137263100_9.

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Kinny, David. "The Agentis Agent InteractionModel." In Intelligent Agents V: Agents Theories, Architectures, and Languages, 331–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-49057-4_22.

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Hempelmann, G., and E. Seidelmayer. "Inotropic Agents/Vasoactive Agents." In Cardiac Anaesthesia: Problems and Innovations, 64–75. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4265-3_7.

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Buchanan, W. J. "Agents." In The Complete Handbook of the Internet, 123–45. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-0-306-48331-8_7.

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Pérez Castaño, Arnaldo. "Agents." In Practical Artificial Intelligence, 91–135. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3357-3_3.

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Bernard, Georges. "Agents." In Principia Economica, 1–9. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-0935-9_1.

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Gonzalez-Perez, Cesar. "Agents." In Information Modelling for Archaeology and Anthropology, 245–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72652-6_23.

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Buchanan, W. J. "Agents." In The Handbook of Data Communications and Networks, 127–50. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4020-7870-5_7.

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O’Brien, Lilian. "Agents." In Philosophy of Action, 136–59. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137317483_9.

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Young, Timothy, Michael Ashcroft, Julian Cooke, Andrew Taylor, John D. Kimball, David W. Martowski, LeRoy Lambert, and Michael F. Sturley. "Agents." In Voyage Charters, 1061. 5th ed. London: Informa Law from Routledge, 2022. http://dx.doi.org/10.4324/9781003046912-64.

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Conference papers on the topic "Agents"

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Azaria, Amos. "Irrational, but Adaptive and Goal Oriented: Humans Interacting with Autonomous Agents." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/813.

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Autonomous agents that interact with humans are becoming more and more prominent. Currently, such agents usually take one of the following approaches for considering human behavior. Some methods assume either a fully cooperative or a zero-sum setting; these assumptions entail that the human's goals are either identical to that of the agent, or their opposite. In both cases, the agent is not required to explicitly model the human’s goals and account for humans' adaptation nature. Other methods first compose a model of human behavior based on observing human actions, and then optimize the agent’s actions based on this model. Such methods do not account for how the human will react to the agent's actions and thus, suffer an overestimation bias. Finally, other methods, such as model free reinforcement learning, merely learn which actions the agent should take at which states. While such methods can, theoretically, account for human adaptation nature, since they require extensive interaction with humans, they usually run in simulation. By not considering the human’s goals, autonomous agents act selfishly, lack generalization, require vast amounts of data, and cannot account for human’s strategic behavior. Therefore, we call for pursuing solution concepts for autonomous agents interacting with humans that consider the human’s goals and adaptive nature.
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Dann, Michael, Yuan Yao, Brian Logan, and John Thangarajah. "Multi-Agent Intention Progression with Black-Box Agents." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/19.

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We propose a new approach to intention progression in multi-agent settings where other agents are effectively black boxes. That is, while their goals are known, the precise programs used to achieve these goals are not known. In our approach, agents use an abstraction of their own program called a partially-ordered goal-plan tree (pGPT) to schedule their intentions and predict the actions of other agents. We show how a pGPT can be derived from the program of a BDI agent, and present an approach based on Monte Carlo Tree Search (MCTS) for scheduling an agent's intentions using pGPTs. We evaluate our pGPT-based approach in cooperative, selfish and adversarial multi-agent settings, and show that it out-performs MCTS-based scheduling where agents assume that other agents have the same program as themselves.
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Barber, K. S., R. M. McKay, C. E. Martin, T. H. Liu, J. Kim, D. Han, and A. Goel. "Sensible Agents in Supply Chain Management: An Example Highlighting Procurement and Production Decisions." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/cie-9078.

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Abstract Agent-based technologies can be applied to many aspects of supply chain management. The need for responsive, flexible agents is pervasive in this environment due to its complex, dynamic nature. Two critical aspects of agent capabilities are the ability to (1) classify agent behaviors according to autonomy level and (2) adapt problem-solving roles to various problem-solving situations during system operation. Sensible Agents, capable of Dynamic Adaptive Autonomy, have been developed to address these issues. A Sensible Agent’s “autonomy level” constitutes a description of the agent’s problem-solving role with respect to a particular goal. Problem-solving roles are defined along a spectrum of autonomy ranging from command-driven, to consensus, to locally autonomous/master. Dynamic Adaptive Autonomy is a capability that allows Sensible Agents to change autonomy levels during system operation to meet the needs of a particular problem-solving situation. This paper provides an overview of the Sensible Agent Testbed and introduces an example supply chain management domain with a scenario showing how this testbed could be used to simulate agent-based problem solving.
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Garcia, Alessandro F., Viviane T. da Silva, Carlos J. P. de Lucena, and Ruy L. Milidiú. "An Aspect-Based Approach for Developing Multi-Agent Object-Oriented Systems." In Simpósio Brasileiro de Engenharia de Software. Sociedade Brasileira de Computação, 2001. http://dx.doi.org/10.5753/sbes.2001.23988.

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Agent technology has been revisited as a complementary approach to the object paradigm in order to design and implement complex distributed software. Objects and agents have many similarities, but agents are also driven by beliefs, goals, capabilities, plans, and a number of agency properties such as autonomy, adaptation, interaction, learning and mobility. Moreover, cooperating software agents must incorporate different collaborative capabilities in order to work together in heterogeneous contexts. In practice, a complex application is composed of objects and multiple types of agents, each of them having distinct agency properties and capabilities. An additional difficulty is that these capabilities and properties typically overlap and interact with each other, and a disciplined scheme to composition is required. This paper discusses software engineering approaches for multi-agent systems, and presents a new approach for building multi-agent object-oriented software from early stage of design. This approach (i) describes structured integration of agents into the object model, (ii) incorporates flexible facilities to build different types of software agents, (iii) encourages the separate handling of each property and capability of an agent, (iv) provides explicit support for disciplined and transparent composition of agency properties and capabilities in complex software agents, and (v) allows the production of agent-based software so that it is easy to understand, maintain and reuse. The proposed approach explores the benefits of aspect-based design and programming for the incorporation of agents in object-oriented systems. We also demonstrate our multi-agent approach through the Portalware system, a web-based environment for the development of e-commerce portals.
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Hegde, Aditya, Vibhav Agarwal, and Shrisha Rao. "Ethics, Prosperity, and Society: Moral Evaluation Using Virtue Ethics and Utilitarianism." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/24.

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Modelling ethics is critical to understanding and analysing social phenomena. However, prior literature either incorporates ethics into agent strategies or uses it for evaluation of agent behaviour. This work proposes a framework that models both, ethical decision making as well as evaluation using virtue ethics and utilitarianism. In an iteration, agents can use either the classical Continuous Prisoner's Dilemma or a new type of interaction called moral interaction, where agents donate or steal from other agents. We introduce moral interactions to model ethical decision making. We also propose a novel agent type, called virtue agent, parametrised by the agent's level of ethics. Virtue agents' decisions are based on moral evaluations of past interactions. Our simulations show that unethical agents make short term gains but are less prosperous in the long run. We find that in societies with positivity bias, unethical agents have high incentive to become ethical. The opposite is true of societies with negativity bias. We also evaluate the ethicality of existing strategies and compare them with those of virtue agents.
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Palmieri, Francesco, Krishna Pattipati, Giovanni Di Gennaro, Amedeo Buonanno, and Martina Merola. "Multiple Agents Interacting via Probability Flows on Factor Graphs." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003761.

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Expert team decision-making demonstrates that effective teams have shared goals, shared mental models to coordinate with minimal communication, establish trust through cross-training, and match task structures through planning. The key questions: Do best practices of human teams translate to hybrid human-AI agent teams, or autonomous agents alone? Is there a mathematical framework for studying shared goals and mental models? We propose factor graphs for studying multi-agent interaction and agile cooperative planning. One promising avenue for modeling interacting agents in real environments is with stochastic approaches, where probability distributions describe uncertainties and imperfect observations. Stochastic dynamic programming provides a framework for modeling multiple agents as scheduled and interacting Markov Decision Processes (MDPs), wherein each agent has partial information about other agents in the team. Each agent acts by accounting for both its objectives and anticipated behaviors of others, even implicitly. We have shown that Dynamic Programming, Maximum likelihood, Maximum entropy and Free-energy-based methods for stochastic control are special cases of probabilistic message propagation rules on modeled factor graphs. Now we show how multiple agents, modeled as multiple interacting factor graphs, exchange probability distributions carrying partial mutual knowledge. We demonstrate the ideas in contexts of moving agents on a discrete grid with obstacles and pre-defined semantic areas (grassy areas, pathways), where each subject has a different destination (goal). The scheduling of agents is fixed a priori or changes over time, and the forward-backward flow for each agent’s MDP is computed every time step, with additional branches that inject probability distributions into and from other agent MDPs. These interactions avoid collisions among agents and enable dynamic planning by agents, accounting for estimates of posterior probabilities of other agents states at future times, the precision and timing being adjustable. Simulations included limited interacting agents (three) on small rectangular discrete grid with starting points and destination goals, obstacles in various positions, narrow passages, small mazes, destinations that require coordination, etc. Solely due to probability distributions flowing in the interacting agent system, the solutions provided by the probabilistic model are interesting because agents that encounter potential conflicts in some regions autonomously adapt strategies, like waiting to let others pass, or taking different paths. The information available to each agent is a combination of rewards received from the environment and inferences about other agents. Previously, we described a scheme for a hierarchy (prioritized order) of agents and unique value function for each agent. Now, we propose a different, tunable interaction, wherein each agent dynamically transmits the posterior probability of its position at future time steps to other agents. The new framework allows flexibility in tuning the information that each agent has on others, ranging from complete knowledge of goals and positions about others out to a limited probabilistic awareness, both in precision and in time, for where others may be located at future time steps. This framework systematically addresses questions, such as the minimal amount of information needed for effective team coordination in the face of changes in goals, communication bandwidth, grid parameters and agent status.
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Alooeff, Eugene, and Dzmitry Adzinets. "Multi-agent system for intelligent scheduling." In 38th ECMS International Conference on Modelling and Simulation. ECMS, 2024. http://dx.doi.org/10.7148/2024-0507.

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This work is dedicated to the development of a multi-agent system for intelligent scheduling: to simulate, to analyze and to optimize used parameters to achieve the best performance in terms of increasing the speed of Technician agents (they provide a field service), reducing transport and time costs for their movement to Service Appointment agents (they are waiting for the Technician agent's active interaction) and Dispatcher agents (they analyze and distribute the relations between another agents. Nowadays the most of the current scheduling models on the market are centralized. This paper exposes a way to use a multi agent-based approach to shift the scheduling system from centralized control to decentralized decisions made by agents. The implemented model allows us to check the model of dynamic scheduling with the real data under a real-time environment and it allows us to test interactions between the agents of three different types.
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Rodriguez, Sebastian, Harsh Deep, Drshika Asher, James Schaffer, and Alex Kirlik. "Validating Trust in Human-Robot Interaction through Virtual Reality: Comparing Embodied and "Behind-the-Screen" Interactions." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004408.

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Human-agent interaction is commonplace in our daily lives, manifesting in forms ranging from virtual assistants on websites to embodied agents like robots that we might encounter in a physical setting. Previous research has largely been focused on “behind-the-screen” interactions, but these might not fully encapsulate the nuanced responses humans exhibit towards physically embodied agents. To address this gap, we use virtual reality to examine how simulated physical embodiment and the reliability of an agent (automated robotic crane) influence trust and performance in a task simulating a quality assurance role and compare it to a “behind-the-screen” interaction. Out of 119 participants, the data revealed there is a marked behavioral shift observed when reliability hits a 91% threshold, with no influence from embodiment. Furthermore, participants displayed a tendency to trust and defer to the decisions of embodied agents more, especially when these agents were not infallible. This study accentuates the need for transparency about an agent's capabilities and emphasizes the significance of ensuring that the agent's representation is congruent with the nature of the interaction. Our findings pave the way for a deeper understanding of human-agent interactions, suggesting a future where these interactions might seamlessly blend the virtual and physical realms.
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Deligkas, Argyrios, Eduard Eiben, Dušan Knop, and Šimon Schierreich. "Individual Rationality in Topological Distance Games Is Surprisingly Hard." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/308.

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In the recently introduced topological distance games, strategic agents need to be assigned to a subset of vertices of a topology. In the assignment, the utility of an agent depends on both the agent's inherent utilities for other agents and its distance from them on the topology. We study the computational complexity of finding individually-rational outcomes; this notion is widely assumed to be the very minimal stability requirement and requires that the utility of every agent in a solution is non-negative. We perform a comprehensive study of the problem's complexity, and we prove that even in very basic cases, deciding whether an individually-rational solution exists is intractable. To reach at least some tractability, one needs to combine multiple restrictions of the input instance, including the number of agents and the topology and the influence of distant agents on the utility.
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LUAN, XIAOCHENG, YUN PENG, and TIMOTHY FININ. "AGENT CONSUMER REPORTS: OF THE AGENTS, BY THE AGENTS, AND FOR THE AGENTS." In Proceedings of the 2nd Asia-Pacific Conference on IAT. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812811042_0012.

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Reports on the topic "Agents"

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Cohen, Philip R. Robust Agent-Based Systems Incorporating Teams of Communicating Agents. Fort Belvoir, VA: Defense Technical Information Center, February 2004. http://dx.doi.org/10.21236/ada421753.

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Chavez, Deborah J., and Joanne F. Tynon. Forest Service special agents, assistant special agents in charge, senior special agents, and supervisory special agents report: nationwide study. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, 2007. http://dx.doi.org/10.2737/psw-rp-255.

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Espinosa, Francisco, and Debraj Ray. Noisy Agents. Cambridge, MA: National Bureau of Economic Research, May 2018. http://dx.doi.org/10.3386/w24627.

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Wiederhold, Gio, Rudi Studer, Mark Musen, Stefan Decker, and Steffen Staab. Onto-Agents-Enabling Intelligent Agents on the Web. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada435112.

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Taylor, C., and C. Wilkerson. Surface polymerization agents. Office of Scientific and Technical Information (OSTI), December 1996. http://dx.doi.org/10.2172/442223.

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Azoulay, Pierre. Agents of Embeddedness. Cambridge, MA: National Bureau of Economic Research, December 2003. http://dx.doi.org/10.3386/w10142.

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Harris, J. Milton. Nucleophilic Decontamination Agents. Fort Belvoir, VA: Defense Technical Information Center, June 1989. http://dx.doi.org/10.21236/ada210637.

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Wright, Robert, Jeffrey Hudack, Nathaniel Gemelli, Steven Loscalzo, and Tsu Kong Lue. Agents Technology Research. Fort Belvoir, VA: Defense Technical Information Center, February 2010. http://dx.doi.org/10.21236/ada516462.

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Rus, Daniela. Mobile Information Agents. Fort Belvoir, VA: Defense Technical Information Center, April 2001. http://dx.doi.org/10.21236/ada387701.

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Childress, Terry A., and Penny L. French. Animal Capture Agents. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada218503.

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