Thematische Bibliographien / Agents and autonomous systems

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Auswahl der wissenschaftlichen Literatur zum Thema „Agents and autonomous systems“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

Zuletzt aktualisiert am 31. Juli 2025

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Zeitschriftenartikel zum Thema "Agents and autonomous systems"

Endriss, Ulle, Ann Nowé, Maria Gini, et al. "Autonomous agents and multiagent systems." AI Matters 7, no. 3 (2021): 29–37. http://dx.doi.org/10.1145/3511322.3511329.

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The 2021 edition of AAMAS, the International Conference on Autonomous Agents and Multiagent Systems, took place from the 3rd to 7th of May 2021 (aamas2021.soton.ac.uk). This year it was organized in the form of a virtual event and attracted over 1,000 registered participants. As every year, the conference featured an exciting programme of contributed talks, keynotes addresses, tutorials, affiliated workshops, a doctoral consortium, and more.

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Bhargava, Hemant K., and William C. Branley. "Simulating belief systems of autonomous agents." Decision Support Systems 14, no. 4 (1995): 329–48. http://dx.doi.org/10.1016/0167-9236(94)00036-r.

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Card, Alexander. "Structure Editors and Autonomous Agents." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 14, no. 1 (2018): 288–89. http://dx.doi.org/10.1609/aiide.v14i1.13007.

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Rational agents are becoming prevalent in many domains, from data analysis to entertainment and games. The increased prevalence of agents has evolved new tools and techniques to work with and design new agents. One such technique is system simulation. Systems simulation is a technique an author can use to imitate tasks, processes, or systems, and in particular, agents. Systems simulation has a variety of uses, ranging from simulating ecological systems to entertainment, such as interactive narratives and digital games. However, many system simulators use specialized programming languages and r

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Košeckà, Jana, and Ruzena Bajcsy. "Discrete Event Systems for autonomous mobile agents." Robotics and Autonomous Systems 12, no. 3-4 (1994): 187–98. http://dx.doi.org/10.1016/0921-8890(94)90025-6.

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Patel, Anjali, Hava Patel, and Charmi Patel. "A Survey on the Evolution of Autonomous Agents: Trends, Challenges, and Future Directions." SPU- Journal of Science, Technology and Management Research II, no. 01 (2025): 58–68. https://doi.org/10.63766/spujstmr.24.000033.

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Over the past few decades, autonomous agents have undergone tremendous evolution, moving from rule based systems to highly adaptive, learning-driven architectures. These autonomously perceivable, reasoning, and acting agents have found use in robotics, healthcare, finance, and other fields. This survey provides a comprehensive overview of the evolution of autonomous agents, highlighting key technological advancements, emerging trends, and persistent challenges. We explore the role of deep reinforcement learning, multi-agent systems, neuro symbolic AI, and edge computing in enhancing agent auto

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Echenim, Jennifer Ifeoma. "Integration of Artificial Intelligence and Blockchain for Intelligent Autonomous Systems." International Journal of Future Engineering Innovations 2, no. 3 (2025): 31–37. https://doi.org/10.54660/ijfei.2025.2.3.31-37.

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The integration of Artificial Intelligence (AI) and Blockchain offers a transformative approach to the development of Intelligent Autonomous Systems (IAS). Autonomous systems, which include self-driving cars, drones, and robots, require advanced decision-making, real-time data processing, and secure communication. AI provides the intelligence necessary for these systems to operate autonomously, while Blockchain introduces decentralized control, transparency, and enhanced security. This paper explores the potential of combining AI and Blockchain technologies to create more secure, transparent,

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JOHNSON, W. LEWIS, and BARBARA HAYES-ROTH. "The First Autonomous Agents Conference." Knowledge Engineering Review 13, no. 2 (1998): 137–42. http://dx.doi.org/10.1017/s0269888998002021.

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The First International Conference on Autonomous Agents brought together researchers concerned with implementing systems that perceive and act in dynamic, unpredictable environments, that coordinate interoperation among complementary component capabilities, and that perform significant jobs with a high degree of autonomy.

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Maes, Pattie. "Modeling Adaptive Autonomous Agents." Artificial Life 1, no. 1_2 (1993): 135–62. http://dx.doi.org/10.1162/artl.1993.1.1_2.135.

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One category of research in Artificial Life is concerned with modeling and building so-called adaptive autonomous agents, which are systems that inhabit a dynamic, unpredictable environment in which they try to satisfy a set of time-dependent goals or motivations. Agents are said to be adaptive if they improve their competence at dealing with these goals based on experience. Autonomous agents constitute a new approach to the study of Artificial Intelligence (AI), which is highly inspired by biology, in particular ethology, the study of animal behavior. Research in autonomous agents has brought

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Dodig-Crnkovic, Gordana, and Mark Burgin. "A Systematic Approach to Autonomous Agents." Philosophies 9, no. 2 (2024): 44. http://dx.doi.org/10.3390/philosophies9020044.

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Agents and agent-based systems are becoming essential in the development of various fields, such as artificial intelligence, ubiquitous computing, ambient intelligence, autonomous computing, and intelligent robotics. The concept of autonomous agents, inspired by the observed agency in living systems, is also central to current theories on the origin, development, and evolution of life. Therefore, it is crucial to develop an accurate understanding of agents and the concept of agency. This paper begins by discussing the role of agency in natural systems as an inspiration and motivation for agent

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Valavanis, K. P. "Autonomous agents [Book Reviews]." IEEE Transactions on Robotics and Automation 15, no. 6 (1999): 1149. http://dx.doi.org/10.1109/tra.1999.817684.

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Dissertationen zum Thema "Agents and autonomous systems"

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,

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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

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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 diversifi

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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

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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 a

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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

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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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Abu, Bakar Badril. "Autonomous multi-agent reconfigurable control systems." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/351346/.

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This thesis is an investigation of methods and architectures for autonomous multi-agent reconfigurable controllers. As part of the analysis two components are looked at: the fault detection and diagnosis (FDD) component and the controller reconfiguration (CR) component. The FDD component detects and diagnoses faults. The CR component on the other hand, adapts or changes the control architecture to accommodate the fault. The problem is to synchronize or integrate these two components in the overall structure of a control system. A novel approach is proposed. A multiagent architecture is used to

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Vizuete, Haro Renato Sebastian. "Contributions to open multi-agent systems : consensus, optimization and epidemics." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST114.

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Dans cette thèse, nous abordons différents problèmes formulés dans un scénario de système multi-agents ouvert (OMAS) où l'ensemble des agents peut changer dans le temps, indépendamment de l'évolution de la dynamique associée au système. Nous considérons des OMAS formulés à l'aide d'un réseau fixe de taille finie, et utilisons deux approches distinctes pour les analyser. Dans la première approche, nous considérons des scénarios caractérisés par l'activation et la désactivation d'agents, de sorte qu'à chaque instant un sous-ensemble différent d'agents actifs peut interagir dans le système. Dans

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LIMA, Allan Diego Silva. "FAct: Um framework para a construção de sistemas multiatores." Universidade Federal de Pernambuco, 2009. https://repositorio.ufpe.br/handle/123456789/1804.

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Made available in DSpace on 2014-06-12T15:52:31Z (GMT). No. of bitstreams: 1 license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009<br>Atores Sintéticos são agentes inteligentes que possuem personalidade, atuam em ambientes multimídias ou virtuais e são representados graficamente por avatares. Estas entidades são utilizadas em sistemas de simuladores como forma de enriquecer a interação entre a aplicação e seus usuários, proporcionando assim aumento da credibilidade do projeto. Com a sua popularização sugiram vários projetos que os utilizam. Est

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Bücher zum Thema "Agents and autonomous systems"

Osman, Nardine, and Carles Sierra, eds. Autonomous Agents and Multiagent Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46840-2.

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Sukthankar, Gita, and Juan A. Rodriguez-Aguilar, eds. Autonomous Agents and Multiagent Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71679-4.

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Sukthankar, Gita, and Juan A. Rodriguez-Aguilar, eds. Autonomous Agents and Multiagent Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71682-4.

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Osman, Nardine, and Carles Sierra, eds. Autonomous Agents and Multiagent Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46882-2.

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Calvaresi, Davide, Amro Najjar, Michael Winikoff, and Kary Främling, eds. Explainable, Transparent Autonomous Agents and Multi-Agent Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51924-7.

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Calvaresi, Davide, Amro Najjar, Michael Schumacher, and Kary Främling, eds. Explainable, Transparent Autonomous Agents and Multi-Agent Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30391-4.

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Gorodetsky, Vladimir, Jiming Liu, and Victor A. Skormin, eds. Autonomous Intelligent Systems: Agents and Data Mining. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b136855.

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Jain, L. C., and Dilip Kumar Pratihar. Intelligent autonomous systems: Foundations and applications. Springer Verlag, 2010.

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Pěchouček, Michal, Simon G. Thompson, and Holger Voos, eds. Defence Industry Applications of Autonomous Agents and Multi-Agent Systems. Birkhäuser Basel, 2008. http://dx.doi.org/10.1007/978-3-7643-8571-2.

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Pěchouček, Michal. Defence industry applications of autonomous agents and multi-agent systems. Birkhäuser, 2008.

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Buchteile zum Thema "Agents and autonomous systems"

Kampik, Timotheus, Juan Carlos Nieves, and Helena Lindgren. "Empathic Autonomous Agents." In Engineering Multi-Agent Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25693-7_10.

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Fukuda, Toshio, and Kosuke Sekiyama. "Cooperative behavior between autonomous agents." In Autonomous Robotic Systems. Springer London, 1998. http://dx.doi.org/10.1007/bfb0030802.

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Purvis, Maryam, Martin Purvis, Azhar Haidar, and Bastin Tony Roy Savarimuthu. "A Distributed Workflow System with Autonomous Components." In Intelligent Agents and Multi-Agent Systems. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32128-6_15.

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Xu, Junhong, Durgakant Pushp, Kai Yin, and Lantao Liu. "Decision-Making Among Bounded Rational Agents." In Distributed Autonomous Robotic Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51497-5_20.

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Boella, Guido, Leendert van der Torre, and Serena Villata. "Changing Institutional Goals and Beliefs of Autonomous Agents." In Intelligent Agents and Multi-Agent Systems. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89674-6_11.

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Shim, Yunju, and Minkoo Kim. "Automatic Short Story Generator Based on Autonomous Agents." In Intelligent Agents and Multi-Agent Systems. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45680-5_11.

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Tzafestas, E. S. "Autonomous Agents in Cellular Manufacturing." In Advances in Intelligent Autonomous Systems. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4790-3_19.

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Márton, Lőrinc, Piroska Haller, Tamás Szabó, Hunor Sándor, Tamás Vajda, and Zoltán Szántó. "Network Controller for Teleoperated Mobile Robotic Agents." In Intelligent Autonomous Systems 13. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08338-4_103.

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Collenette, Joe, Katie Atkinson, Daan Bloembergen, and Karl Tuyls. "Modelling Mood in Co-operative Emotional Agents." In Distributed Autonomous Robotic Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73008-0_39.

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Red’ko, Vladimir G. "Models of Autonomous Cognitive Agents." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32554-5_2.

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Konferenzberichte zum Thema "Agents and autonomous systems"

Marza, Pierre, Laetitia Matignon, Olivier Simonin, Dhruv Batra, Christian Wolf, and Devendra S. Chaplot. "AutoNeRF: Training Implicit Scene Representations with Autonomous Agents." In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2024. https://doi.org/10.1109/iros58592.2024.10802101.

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Murillo, Ana C. "Principled Pathways Towards Autonomy and Emergence in Agents." In 2025 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2025. https://doi.org/10.1109/icarsc65809.2025.10970125.

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Jabbarpour, Mohammad, Ghaith El-Dalahmeh, Bao Vo, and Ryszard Kowalczyk. "Intelligent Health & Mission Management Architecture for Autonomous and Resilient Distributed Space Systems." In 17th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013094600003890.

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Sudo, Yasuhiro, Keisuke Kasiwase, and Michiko Matsuda. "Verification of Scheduling Efficiency of an Autonomous Assembly System Using the Multi-Agent Manufacturing Simulator." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7231.

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This study is an examination of the effect of agent-based autonomous production scheduling, using the virtual factory on multi-agent simulation system. In the autonomous manufacturing system, a production plan is generated autonomously and dynamically, using communication and negotiation between agents that correspond to factory components. As infrastructure software for agent based manufacturing, the artisoc(c) is used as multi-agent simulator system. In this virtual factory, three types of agents are equipped. Users can operate a configuration such as input new jobs, adjusting a machine sett

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Minarsch, David, Seyed Ali Hosseini, Marco Favorito, and Jonathan Ward. "Trading Agent Competition with Autonomous Economic Agents." In Special Session on Super Distributed and Multi-agent Intelligent Systems. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010431805740582.

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Wang, Shilong, Jian Yi, Xia Hong, and Z. Zhang. "Heterogeneous Autonomous Agent Architecture for Agile Manufacturing." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/cie-34397.

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Considering the agent-based modeling and mapping in manufacturing system, some system models are described in this paper, which are included: Domain Based Hierarchical Structure (DBHS), Cascading Agent Structure (CAS), Proximity Relation structure (PRS), and Bus-based network structure (BNS). In DBHS, one sort of agents, called static agents, individually acts as Domain Agents, Resources Agents, UserInterface Agents and Gateway Agents. And the others, named mobile agents, are the brokers of task and process flow. Static agents representing a subsystem may itself be an agent-based network and s

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Zhang, Guoxian, Devendra P. Garg, and Greg Fricke. "Hazardous Spill Perimeter Detection and Monitoring via Multiple Autonomous Mobile Robotic Agents." In ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4160.

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The problem of perimeter detection and monitoring has a variety of applications. In this paper, a hybrid system with finite states strategy is proposed for multiple autonomous robotic agents with the purpose of hazardous spill perimeter detection and tracking. In the system, each robotic agent is assumed to be in one of the following states: searching, pursuing, and tracking. The agents are prioritized based on their states, and a potential field is constructed for agents in each state. The location and velocity of an agent in the tracking state as well as those of its closest leading and trai

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Mostafa, Salama A., Mohd Sharifuddin Ahmad, Azhana Ahmad, Muthukkaruppan Annamalai, and Saraswathy Shamini Gunasekaran. "An autonomy viability assessment matrix for agent-based autonomous systems." In 2015 International Symposium on Agents, Multi-Agent Systems and Robotics (ISAMSR). IEEE, 2015. http://dx.doi.org/10.1109/isamsr.2015.7379130.

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Hagras, H., and M. Colley. "Collaborating multi robotic agents for operations in inaccessible environments." In IEE Forum on: Autonomous Systems. IEE, 2005. http://dx.doi.org/10.1049/ic:20050470.

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Wu, H. "Multi-agent based automation platform for distributed industrial systems." In IEE Seminar on Autonomous Agents in Control. IEE, 2005. http://dx.doi.org/10.1049/ic:20050179.

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Berichte der Organisationen zum Thema "Agents and autonomous systems"

Shen, Wei-Min. Self-Organizing and Autonomous Learning Agents and Systems. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada430491.

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Lohn, Andrew, Anna Knack, Ant Burke, and Krystal Jackson. Autonomous Cyber Defense. Center for Security and Emerging Technology, 2023. http://dx.doi.org/10.51593/2022ca007.

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The current AI-for-cybersecurity paradigm focuses on detection using automated tools, but it has largely neglected holistic autonomous cyber defense systems — ones that can act without human tasking. That is poised to change as tools are proliferating for training reinforcement learning-based AI agents to provide broader autonomous cybersecurity capabilities. The resulting agents are still rudimentary and publications are few, but the current barriers are surmountable and effective agents would be a substantial boon to society.

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Toner, Helen, John Bansemer, Kyle Crichton, et al. Through the Chat Window and Into the Real World: Preparing for AI Agents. Center for Security and Emerging Technology, 2024. http://dx.doi.org/10.51593/20240034.

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Computer scientists have long sought to build systems that can actively and autonomously carry out complicated goals in the real world—commonly referred to as artificial intelligence "agents." Recently, significant progress in large language models has fueled new optimism about the prospect of building sophisticated AI agents. This CSET-led workshop report synthesizes findings from a May 2024 workshop on this topic, including what constitutes an AI agent, how the technology is improving, what risks agents exacerbate, and intervention points that could help.

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Chen, Guang. Multi-agent Collaborative Perception for Autonomous Driving: Unsettled Aspects. SAE International, 2023. http://dx.doi.org/10.4271/epr2023017.

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<div class="section abstract"><div class="htmlview paragraph">This report delves into the field of multi-agent collaborative perception (MCP) for autonomous driving: an area that remains unresolved. Current single-agent perception systems suffer from limitations, such as occlusion and sparse sensor observation at a far distance.</div><div class="htmlview paragraph"><b>Multi-agent Collaborative Perception for Autonomous Driving: Unsettled Aspects</b> addresses three unsettled topics that demand immediate attention: <ul class="list disc"><li class="li

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Shen, Shiyu, Yuhui Zhai, and Yanfeng Ouyang. Planning and Dynamic Management of Autonomous Modular Mobility Services. Illinois Center for Transportation, 2024. https://doi.org/10.36501/0197-9191/24-029.

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As we enter the next era of autonomous driving, robo-vehicles (which serve as low-cost and fully compliant drivers) are replacing conventional chauffeured services in the mobility market. During just the last few years, companies like Waymo Inc. and Cruise Inc. have already offered fully driverless robo-taxi services to the general public in cities like Phoenix and San Francisco. The rapid evolution of autonomous vehicles is anticipated to reshape the shared mobility market very soon. This project aims to address the following open questions. At the operational level, how should modular units

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Smith, Clint, Andmorgan Fischer, Alex Ly, and Michael Anderson. Autonomous QUerying and PATHogen threat agent sensor system (AQUA PATH) : monitoring source waters with geospatially wirelessly networked distributed sensing systems. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/37533.

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Bozzo Hauri, Sebastián. The New Frontier of Civil Liability: Artificial Intelligence, Autonomy, and Consumer Protection. Carver University; Universidad Autónoma de Chile, 2025. https://doi.org/10.32457/bozzo2202599.

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Technological evolution has entered a phase that challenges the very foundations of private law. The emergence of systems based on artificial intelligence (AI)—particularly in their most recent form, so-called AI agents—compels a reassessment of the traditional framework of civil liability, especially in the field of consumer law. The trajectory of AI has followed a path marked by three distinct waves. The first wave was predictive AI, trained on historical data to anticipate future behavior, as seen in recommendation engines and segmentation models. The second wave introduced generative AI—su

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Pasupuleti, Murali Krishna. Optimal Control and Reinforcement Learning: Theory, Algorithms, and Robotics Applications. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv225.

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Abstract: Optimal control and reinforcement learning (RL) are foundational techniques for intelligent decision-making in robotics, automation, and AI-driven control systems. This research explores the theoretical principles, computational algorithms, and real-world applications of optimal control and reinforcement learning, emphasizing their convergence for scalable and adaptive robotic automation. Key topics include dynamic programming, Hamilton-Jacobi-Bellman (HJB) equations, policy optimization, model-based RL, actor-critic methods, and deep RL architectures. The study also examines traject

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Occhiali, Giovanni, and Fredrick Kalyango. Can Tax Agents Support Tax Compliance in Low-Income Countries? A Review of the Literature and some Preliminary Evidence from Uganda. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/ictd.2021.018.

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Since the late 1970s, many countries have based their tax systems on self-assessment – taxpayers are expected to evaluate their liabilities autonomously, and voluntarily remit their tax due. If the tax system is perceived as fair and easy to navigate, with credible threat of penalisation for non-compliance, self-assessment reduces the cost of tax administration without significant revenue losses (Barr et al. 1977; Teviotdale and Thompson 1999; James and Alley 2004). On the other hand, self-assessment entails an increase in compliance costs for taxpayers, at the very least in terms of time spen

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Langley, Pat, Kevin Thompson, Wayne Iba, John H. Gennari, and John A. Allen. An Integrated Cognitive Architecture for Autonomous Agents. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada225701.

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