Auswahl der wissenschaftlichen Literatur zum Thema „Multi-agent interaction“
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Zeitschriftenartikel zum Thema "Multi-agent interaction"
Lorkiewicz,, Wojciech, und Radosław Katarzyniak. „Multi-participant Interaction in Multi-agent Naming Game“. Computational Methods in Science and Technology 20, Nr. 2 (2014): 59–60. http://dx.doi.org/10.12921/cmst.2014.20.02.59-80.
Der volle Inhalt der QuelleLi, Guangyu, Bo Jiang, Hao Zhu, Zhengping Che und Yan Liu. „Generative Attention Networks for Multi-Agent Behavioral Modeling“. Proceedings of the AAAI Conference on Artificial Intelligence 34, Nr. 05 (03.04.2020): 7195–202. http://dx.doi.org/10.1609/aaai.v34i05.6209.
Der volle Inhalt der QuellePenner, Robin R. „Multi-Agent Societies for Collaborative Interaction“. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, Nr. 15 (Oktober 1996): 762–66. http://dx.doi.org/10.1177/154193129604001503.
Der volle Inhalt der QuelleBoella, Guido, Joris Hulstijn und Leendert van der Torre. „Interaction in Normative Multi-Agent Systems“. Electronic Notes in Theoretical Computer Science 141, Nr. 5 (Dezember 2005): 135–62. http://dx.doi.org/10.1016/j.entcs.2005.05.020.
Der volle Inhalt der QuelleCHEREMISINOV, Dmitri. „The Specification of Agent Interaction in Multi-Agent Systems“. Intelligent Information Management 01, Nr. 02 (2009): 65–72. http://dx.doi.org/10.4236/iim.2009.12011.
Der volle Inhalt der QuelleDushkin, Roman. „Multi-agent systems for cooperative ITS“. Тренды и управление, Nr. 1 (Januar 2021): 42–50. http://dx.doi.org/10.7256/2454-0730.2021.1.34169.
Der volle Inhalt der QuelleMurakami, Yohei, Toru Ishida, Tomoyuki Kawasoe und Reiko Hishiyama. „Multi-Agent Simulation Based on Interaction Design.“ Transactions of the Japanese Society for Artificial Intelligence 18 (2003): 278–85. http://dx.doi.org/10.1527/tjsai.18.278.
Der volle Inhalt der QuellePoslad, Stefan. „Specifying protocols for multi-agent systems interaction“. ACM Transactions on Autonomous and Adaptive Systems 2, Nr. 4 (November 2007): 15. http://dx.doi.org/10.1145/1293731.1293735.
Der volle Inhalt der QuelleZhou, Wenhong, Jie Li, Yiting Chen und Lin-Cheng Shen. „Strategic Interaction Multi-Agent Deep Reinforcement Learning“. IEEE Access 8 (2020): 119000–119009. http://dx.doi.org/10.1109/access.2020.3005734.
Der volle Inhalt der QuelleVogel-Heuser, Birgit, Matthias Seitz, Luis Alberto Cruz Salazar, Felix Gehlhoff, Alaettin Dogan und Alexander Fay. „Multi-agent systems to enable Industry 4.0“. at - Automatisierungstechnik 68, Nr. 6 (25.06.2020): 445–58. http://dx.doi.org/10.1515/auto-2020-0004.
Der volle Inhalt der QuelleDissertationen zum Thema "Multi-agent interaction"
Chen, Xudong. „Multi-Agent Systems with Reciprocal Interaction Laws“. Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11424.
Der volle Inhalt der QuelleEngineering and Applied Sciences
Kalenka, Susanne. „Modelling social interaction attitudes in multi-agent systems“. Thesis, Queen Mary, University of London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.395937.
Der volle Inhalt der QuellePerez, Jorge (Jorge I. ). „Designing interaction for human-machine collaboration in multi-agent scheduling“. Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/106007.
Der volle Inhalt der QuelleThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 57-58).
In the field of multi-agent task scheduling, there are many algorithms that are capable of minimizing objective functions when the user is able to specify them. However, there is a need for systems and algorithms that are able to include user preferences or domain knowledge into the final solution. This will increase the usability of algorithms that would otherwise not include some characteristics desired by the end user but are highly optimal mathematically. We hypothesize that allowing subjects to iterate over solutions while adding allocation and temporal constraints would allow them to take advantage of the computational power to solve the temporal problem while including their preferences. No statistically significant results were found that supported that such algorithm is preferred over manually solving the problem among the participants. However, there are trends that support the hypothesis. We found statistically significant evidence (p=0.0027), that subjects reported higher workload when working with Manual Mode and Modification Mode rather than Iteration Mode and Feedback Iteration Mode. We propose changes to the system that can provide guidance for future design of interaction for scheduling problems.
by Jorge Perez.
M. Eng.
Bai, Xi. „Peer-to-peer, multi-agent interaction adapted to a web architecture“. Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/7968.
Der volle Inhalt der QuelleAnacleto, Louçã Jorge. „Cartographie cognitive, réflexion stratégique et interaction distribuée : une approche multi-agent“. Paris 9, 2000. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=2000PA090028.
Der volle Inhalt der QuelleDinu, Razvan. „Web Agents : towards online hybrid multi-agent systems“. Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20126/document.
Der volle Inhalt der QuelleMulti-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
Scown, Philip J. A. „Knowledge needs analysis for simultaneously multi-agent real-time systems“. Thesis, Loughborough University, 1997. https://dspace.lboro.ac.uk/2134/26859.
Der volle Inhalt der QuelleGRALHOZ, RICARDO AUGUSTO RODRIGUES. „LAWML: A LANGUAGE FOR MODELING INTERACTION LAWS IN OPEN MULTI-AGENT SYSTEMS“. PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=11626@1.
Der volle Inhalt der QuelleO paradigma de agentes surgiu visando atender à necessidade de novas abstrações para o desenvolvimento de sistemas complexos e distribuídos. Para lidar com a mprevisibilidade do comportamento dos sistemas multi-agentes abertos, que são sistemas concorrentes e assíncronos formados por diversos agentes que agem com certo grau de autonomia e que podem interagir entre si para alcançar objetivos individuais, são usados mecanismos de governança na regulação das interações. Na maioria das abordagens existentes, a especificação das regras de governança é feita com o uso de linguagens declarativas ou de novas representações gráficas, o que pode tornar custosa essa tarefa e dificultar o uso desses mecanismos de governança. Esta dissertação apresenta a LawML, uma linguagem de modelagem baseada em UML para a especificação das regras de interação entre os agentes, com o objetivo de facilitar a tarefa de modelagem e, portanto, facilitar o uso de um mecanismo específico de governança baseado em leis de interação. Um conjunto de regras de transformação é apresentado junto com a linguagem, para permitir que os modelos gráficos de lei de interação sejam transformados em código no formato XMLaw - a linguagem declarativa do mecanismo de governança. Baseada nessas regras de transformação, é apresentada a ferramenta LawGenerator de transformação automática dos modelos de lei, para permitir o desenvolvimento das leis de interação com o foco nos modelos. E, por fim, esta abordagem é aplicada em um estudo baseado em um caso real de sistema distribuído com as características de um sistema multi-agente aberto - o SELIC, do Banco Central do Brasil.
The paradigm of agents appeared while aiming to satisfy the need for new abstractions for the development of complex and distributed systems. To manage with the unpredictable behavior of open multi-agent systems, governance mechanisms are used in the regulation of interactions between agents. This is due to the concurrent and asynchronous characteristics of these systems, which are formed by several agents who can act autonomically and can interact with each other to reach individual goals. In the majority of approaches, the governance rules are specified with declarative languages or new graphical representations, which can make this task costly and can make the use of these governance mechanisms difficult. This essay presents the LawML, a modeling language based on UML for the specification of rules for interactions between agents, which is aimed to facilitate the modeling task and, therefore, to facilitate the use of a specific governance mechanism based on interaction laws. A set of transformation rules is presented in addition to the language to allow the graphical interaction law models to be transformed into the declarative language of the governance mechanism, the XMLaw format code. To allow the model-driven development of interaction laws, it is presented the LawGenerator, a tool for the automatic transformation of the law model, based on these transformation rules. Finally, this approach is applied to a case study based on a real distributed system, the Brazilian Central Bank SELIC system, with the characteristics of an open multi-agent system.
Cunningham, Bryan. „Non-Reciprocating Sharing Methods in Cooperative Q-Learning Environments“. Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/34610.
Der volle Inhalt der QuelleMaster of Science
Salge, Christoph. „Information theoretic models of social interaction“. Thesis, University of Hertfordshire, 2013. http://hdl.handle.net/2299/13887.
Der volle Inhalt der QuelleBücher zum Thema "Multi-agent interaction"
1960-, Sun Ron, Hrsg. Cognition and multi-agent interaction: From cognitive modeling to social simulation. Cambridge: Cambridge University Press, 2006.
Den vollen Inhalt der Quelle findenKhosla, Rajiv. Intelligent Multimedia Multi-Agent Systems: A Human-Centered Approach. Boston, MA: Springer US, 2000.
Den vollen Inhalt der Quelle findenWayne, Wobcke, Sen Sandip, Sugawara Toshiharu und SpringerLink (Online service), Hrsg. PRIMA 2012: Principles and Practice of Multi-Agent Systems: 15th International Conference, Kuching, Sarawak, Malaysia, September 3-7, 2012. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Den vollen Inhalt der Quelle findenIyad, Rahwan, Parsons Simon und SpringerLink (Online service), Hrsg. Argumentation in Multi-Agent Systems: 7th International Workshop, ArgMAS 2010 Toronto, ON, Canada, May 10, 2010 Revised, Selected and Invited Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.
Den vollen Inhalt der Quelle findenInternational Conference on Multi-Agent Systems (1st 1995 San Francisco, Calif.). ICMAS--95, First International Conference on Multi-Agent Systems: Proceedings, June 12-14, 1995, San Francisco, California. Menlo Park, Calif: AAAI Press, 1995.
Den vollen Inhalt der Quelle findenSun, Ron, Hrsg. Cognition and Multi-Agent Interaction. Cambridge University Press, 2005. http://dx.doi.org/10.1017/cbo9780511610721.
Der volle Inhalt der QuelleW, Brockett Roger, Tarokh Vahid und Lu Yue, Hrsg. Multi-Agent Systems with Reciprocal Interaction Laws. 2014.
Den vollen Inhalt der Quelle findenSun, Ron. Cognition and Multi-agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press, 2006.
Den vollen Inhalt der Quelle findenSun, Ron. Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press, 2008.
Den vollen Inhalt der Quelle findenSun, Ron. Cognition and Multi-Agent Interaction: From Cognitive Modeling to Social Simulation. Cambridge University Press, 2005.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Multi-agent interaction"
Torii, Daisuke, Toru Ishida, Stéphane Bonneaud und Alexis Drogoul. „Layering Social Interaction Scenarios on Environmental Simulation“. In Multi-Agent and Multi-Agent-Based Simulation, 78–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32243-6_7.
Der volle Inhalt der QuelleChen, Hongbing, Qun Yang und Manwu Xu. „A Calculus for MAS Interaction Protocol“. In Agent Computing and Multi-Agent Systems, 22–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11802372_6.
Der volle Inhalt der QuelleKlügl, Franziska. „Affordance-Based Interaction Design for Agent-Based Simulation Models“. In Multi-Agent Systems, 51–66. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17130-2_4.
Der volle Inhalt der QuelleMichel, Fabien, Abdelkader Gouaïch und Jacques Ferber. „Weak Interaction and Strong Interaction in Agent Based Simulations“. In Multi-Agent-Based Simulation III, 43–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24613-8_4.
Der volle Inhalt der QuelleEl Fallah-Seghrouchni, Amal, Serge Haddad und Hamza Mazouzi. „Protocol Engineering for Multi-agent Interaction“. In Multi-Agent System Engineering, 89–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48437-x_8.
Der volle Inhalt der QuelleTanaka, Rie, Hideyuki Nakanishi und Toru Ishida. „Coordination of Concurrent Scenarios in Multi-agent Interaction“. In Agent Computing and Multi-Agent Systems, 293–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11802372_29.
Der volle Inhalt der QuelleLin, Aizhong. „Strategic Multi-Personal-Agent Interaction“. In Lecture Notes in Computer Science, 93–107. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44637-0_7.
Der volle Inhalt der QuelleTagiew, Rustam. „Multi-Agent-System for General Strategic Interaction“. In Agent and Multi-Agent Systems: Technologies and Applications, 649–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01665-3_65.
Der volle Inhalt der QuelleZatelli, Maicon Rafael, und Jomi Fred Hübner. „The Interaction as an Integration Component for the JaCaMo Platform“. In Engineering Multi-Agent Systems, 431–50. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14484-9_22.
Der volle Inhalt der QuelleFerrando, Angelo, Michael Winikoff, Stephen Cranefield, Frank Dignum und Viviana Mascardi. „On Enactability of Agent Interaction Protocols: Towards a Unified Approach“. In Engineering Multi-Agent Systems, 43–64. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51417-4_3.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Multi-agent interaction"
Bel-Enguix, Gemma, und M. Dolores Jimenez-Lopez. „Agent-environment interaction in a multi-agent system“. In the 2007 GECCO conference companion. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1274000.1274045.
Der volle Inhalt der QuelleSeitbekova, Yerkezhan, und Timur Bakibayev. „Predator-Prey Interaction Multi-Agent Modelling“. In 2018 IEEE 12th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2018. http://dx.doi.org/10.1109/icaict.2018.8747087.
Der volle Inhalt der QuelleMostafa, Salama A., Mohd Sharifuddin Ahmad, Azhana Ahmad, Muthukkaruppan Annamalai und Saraswathy Shamini Gunasekaran. „A Flexible Human-Agent Interaction model for supervised autonomous systems“. In 2016 2nd International Symposium on Agent, Multi-Agent Systems and Robotics (ISAMSR). IEEE, 2016. http://dx.doi.org/10.1109/isamsr.2016.7810011.
Der volle Inhalt der QuelleVillani, Valeria, Lorenzo Sabattini, Cristian Secchi und Cesare Fantuzzi. „Natural interaction based on affective robotics for multi-robot systems“. In 2017 International Symposium on Multi-Robot and Multi-Agent Systems (MRS). IEEE, 2017. http://dx.doi.org/10.1109/mrs.2017.8250931.
Der volle Inhalt der QuelleJansma, Walter, Elia Trevisan, Álvaro Serra-Gómez und Javier Alonso-Mora. „Interaction-Aware Sampling-Based MPC with Learned Local Goal Predictions“. In 2023 International Symposium on Multi-Robot and Multi-Agent Systems (MRS). IEEE, 2023. http://dx.doi.org/10.1109/mrs60187.2023.10416788.
Der volle Inhalt der Quelle„Enabling Spoken Dialogue Interaction About Team Activities“. In The First International Workshop on Multi-Agent Robotic Systems. SciTePress - Science and and Technology Publications, 2005. http://dx.doi.org/10.5220/0001196400230030.
Der volle Inhalt der QuelleOrlic, M., B. Mihaljevic und M. Zagar. „Modelling interaction scenarios in multi-agent systems“. In 28th International Conference on Information Technology Interfaces, 2006. IEEE, 2006. http://dx.doi.org/10.1109/iti.2006.1708509.
Der volle Inhalt der QuelleKubera, Yoann, Philippe Mathieu und Sébastien Picault. „Interaction Selection Ambiguities in Multi-agent Systems“. In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2008. http://dx.doi.org/10.1109/wiiat.2008.260.
Der volle Inhalt der QuelleStaley, James, und Elaine Schaertl Short. „Contingency Detection in Multi-Agent Interactions“. In HRI '21: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3434074.3447164.
Der volle Inhalt der QuelleChen, Shuyi, Masatoshi Hanai, Zhengchang Hua, Nikos Tziritas und Georgios Theodoropoulos. „Efficient Direct Agent Interaction in Optimistic Distributed Multi-Agent-System Simulations“. In SIGSIM-PADS '20: SIGSIM Principles of Advanced Discrete Simulation. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3384441.3395977.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Multi-agent interaction"
Spears, William, Diana Spears, Wesley Kerr, Suranga Hettiarachchi und Dimitri Zarzhitsky. Optimizing Interaction Potentials for Multi-Agent Surveillance. Fort Belvoir, VA: Defense Technical Information Center, Januar 2004. http://dx.doi.org/10.21236/ada434929.
Der volle Inhalt der QuelleRoszman, Larry, Derek Armstrong, Aram Khalali und Gwen Hickling. Dynamic Control and Formal Models of Multi-Agent Interactions and Behaviors. Fort Belvoir, VA: Defense Technical Information Center, Mai 2005. http://dx.doi.org/10.21236/ada435125.
Der volle Inhalt der QuelleCoble, Jeff, Larry Roszman und Tiffany Frazier. Dynamic Control and Formal Models of Multi-Agent Interactions and Behaviors. Fort Belvoir, VA: Defense Technical Information Center, Februar 2003. http://dx.doi.org/10.21236/ada412536.
Der volle Inhalt der QuelleManulis, Shulamit, Christine D. Smart, Isaac Barash, Guido Sessa und Harvey C. Hoch. Molecular Interactions of Clavibacter michiganensis subsp. michiganensis with Tomato. United States Department of Agriculture, Januar 2011. http://dx.doi.org/10.32747/2011.7697113.bard.
Der volle Inhalt der QuelleFicht, Thomas, Gary Splitter, Menachem Banai und Menachem Davidson. Characterization of B. Melinensis REV 1 Attenuated Mutants. United States Department of Agriculture, Dezember 2000. http://dx.doi.org/10.32747/2000.7580667.bard.
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