Multiagent Systems: A Survey from a Machine Learning Perspective

Stone, Peter, Veloso, Manuela·2000·Autonomous Robots

Cited by (1,001)

Items 701–800 of 1,001

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    Helmut Jarosch · 2009 · RePEc: Research Papers in Economics
  2. Potential-Based Reward Shaping for Knowledge-Based, Multi-Agent Reinforcement Learning
    Sam Devlin · 2013 · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)
  3. Being Reactive by Exchanging Roles: An Empirical Study
    Olivier Sigaud, Pierre Gérard · 2001 · Lecture notes in computer science
  4. A layered approach for an autonomous robotic soccer system
    Manuela Veloso, Peter Stone, Sorin Achim · 1997
  5. DESIGN AND INTEGRATION OF AGENT-BASED PARTIAL BRAIN MODELS FOR ROBOTIC SYSTEMS BY MEANS OF HIERARCHICAL COOPERATIVE COEVOLUTION
    Michail Maniadakis · 2006
  6. A Multi-Agent Framework for Collaborative Reasoning
    Angela Goh, Chunyan Miao, Yuan Miao · 2002 · Intelligent Systems
  7. Attentional Policies for Cross-Context Multi-Agent Reinforcement Learning
    Matthew A. Wright, Roberto Horowitz · 2019 · arXiv (Cornell University)
  8. Efficient Distributed Training through Gradient Compression with Sparsification and Quantization Techniques
    Shruti Singh, Shantanu Kumar · 2024 · arXiv (Cornell University)
  9. HCC Architecture - Hormonal Communications and Control Architecture
    Paul R. Thompson · 2004 · RIT Scholar Works (Rochester Institute of Technology)
  10. Commande prédictive sous contraintes de sécurité pour des systèmes dynamiques Multi-Agents
    Minh Tri Nguyen · 2016 · theses.fr (ABES)
  11. LEGOMem: Modular Procedural Memory for Multi-agent LLM Systems for Workflow Automation
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  12. Multi-agent based railway track management System
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  17. Sustainable Safety in Mobile Multi-robot Systems via Collective Adaptation
    Darko Bozhinoski, Ivano Malavolta, Antonio Bucchiarone, Annapaola Marconi · 2015 · IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
  18. Kooperierende Mobile Roboter
    Sven Behnke · 2013 · at - Automatisierungstechnik
  19. A SOM-BASED MULTI-AGENT ARCHITECTURE FOR MULTIROBOT SYSTEMS
    Anmin Zhu, Simon X. Yang · 2006 · International Journal of Robotics and Automation
  20. Reputation-Based Distributed Coordination for Heterogeneous Autonomous Agents
    Predrag T. Tošić · 2016 · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
  21. Intelligent, Autonomous, and Multi-Agents
    Taye Iyinoluwa Adeyinka, Kehinde Iyioluwa Adeyinka · 2025 · Advances in computational intelligence and robotics book series
  22. Cooperation in a distributed hybrid potential-field/reinforcement learning multi-agents-based autonomous path planning in a dynamic time-varying unstructured environment
    Dalila B. Megherbi, Vikram Malayia · 2012 · IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support
  23. Multi-agent Decision Model and Application Based on Recurrent Neural Network and Particle Swarm Optimization
    Ming Li, Weibing Liu, Xianjia Wang · 2008 · International Conference on Natural Computation (ICNC)
  24. Concurrent agent‐based evolutionary computations as adaptive dataflows
    Daniel Krzywicki, Łukasz Faber, R. J. Debski · 2018 · Concurrency and Computation Practice and Experience
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    Шихин Владимир Анатольевич, Amin Kamal Abd Elraheem, J. Ren · 2018 · International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)
  26. Modeling and Analysis of Autonomous Agents’ Decisions in Learning to Cross a Cellular Automaton-Based Highway
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  27. Behavior Selection System for Human–Robot Cooperation using Tensor SOM
    Moeko Tominaga, Yasunori Takemura, Kazuo Ishii · 2020 · Journal of Robotics Networking and Artificial Life
  28. A Generalized Dynamic Potential Energy Model for Multiagent Path Planning
    Liu He, Haoning Xi, Tangyi Guo, Kun Tang · 2020 · Journal of Advanced Transportation
  29. Computable Law as Argumentation-based MAS
    Roberta Calegari, Andrea Omicini, Giovanni Sartor B · 2020 · Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)
  30. Research on Workers Integration in Smart Factories With Multi-Agent Control System
    Zequn Zhang, Dunbing Tang, Qingwei Nie · 2021 · IEEE Access
  31. Cooperative Multiagent Attentional Communication for Large‐Scale Task Space
    Qijie Zou, Youkun Hu, Dewei Yi, Bing Gao, Jing Qin · 2022 · Wireless Communications and Mobile Computing
  32. Optimization of Fluid Modeling and Flow Control Processes Using Machine Learning: A Brief Review
    Surbhi Razdan, Sarth Shah · 2022 · Lecture notes in mechanical engineering
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    Yu Wang, Ke Fu, Hao Chen, Quan Liu, Jian Huang, Zhongjie Zhang · 2022 · Applied Sciences
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    Hyo-June Lee, Woo-Seok Jang, Seong-Jin Lee, Donggyu Kim · 2023 · The Journal of Korean Institute of Information Technology
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    Kléber Cabral, Jean-Alexis Delamer, Camille Alain Rabbath, Nicolas Lechevin, Craig Williams, Sidney Nascimento Givigi · 2024 · International Conference on Unmanned Aircraft Systems (ICUAS)
  36. Decision Tree Pruning Using Expert Knowledge
    Jingfeng Cai · 2008 · OhioLink ETD Center (Ohio Library and Information Network)
  37. A Multi-Agent System to Assist with Property Valuation Using Heterogeneous Ensembles of Fuzzy Models
    Magdalena Graczyk, Tadeusz Lasota, Zbigniew Telec, Bogdan Trawiński · 2010 · Lecture notes in computer science
  38. Collaborating and Learning Predators on a Pursuit Scenario
    Nugroho Fredivianus, Urban Richter, Hartmut Schmeck · 2010 · IFIP International Federation for Information Processing/IFIP
  39. Model-Based Reinforcement Learning in Multiagent Systems with Sequential Action Selection
    Ali Akramizadeh, Ahmad Afshar, Mohammad Bagher Menhaj, Samira Jafari · 2011 · IEICE Transactions on Information and Systems
  40. Learning acceleration by policy sharing
    Kao‐Shing Hwang, Yu-Jen Chen, Wei‐Cheng Jiang · 2011 · World Congress on Intelligent Control and Automation
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    Tony White · 2005
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    Farzaneh Ghorbani, Mohsen Afsharchi, Vali Derhami · 2019 · Journal of Intelligent & Fuzzy Systems
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    Philip R. Cook · 2007 · ScholarsArchive (Brigham Young University)
  44. Distributed collaborative system for heterogeneous swarms of autonomous mobile robots
    Vincent Autefage, Serge Chaumette B, Damien Magoni · 2015 · International Conference on Protocol Engineering and International Conference on New Technologies of Distributed Systems (ICPE-NTDS)
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  47. A study of group size and communication in an evolving fuzzy-controlled population
    Sam McKennoch, S. Hoyt, Linda G. Bushnell · 2005 · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
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    Vineet Nagrath, Olivier Morel, Aamir Saeed Malik, Muhammad Naufal Bin muhammad Saad, Fabrice Mériaudeau · 2015 · Peer-to-Peer Networking and Applications
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    Liang Peng, Hai Liu · 2007 · IEEE International Conference on Robotics and Biomimetics (ROBIO)
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    Shibata Ko, Munehiro Takimoto, Yasushi Kambayashi · 2014 · Advances in intelligent systems and computing
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    Neha Satak, John E. Hurtado · 2014 · AIAA Aerospace Sciences Meeting
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    Ruba Obiedat, Mohammad Reza Faisal, Hossam Faris, Osama Harfoushi, Saham A. Nawafleh · 2013 · Scientific Research and Essays
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    Che G. Ngufor · 2014
  68. GEOMETRIC TASK DECOMPOSITION IN A MULTI-AGENT ENVIRONMENT
    Kaivan Kamali, Dan A. Ventura, A.K. Garga, Soundar R. T. Kumara · 2006 · Applied Artificial Intelligence
  69. Fielded object networks as a framework for computer intelligence
    R. Goncalves, Fernando A. C. Gomide, Ricardo Gudwin · 2002
  70. A biologically-inspired platform for the evolution of communication in multi-agent systems
    Sam McKennoch, John-Michael McNew, Linda G. Bushnell · 2003 · The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications
  71. On Learning How to Communicate Over Noisy Channels for Collaborative Tasks.
    Arsham Mostaani, Osvaldo Simeone · 2018 · arXiv (Cornell University)
  72. Using Multi-Agent Reinforcement Learning in Auction Simulations
    Medet Kanmaz, Elif Sürer · 2020 · arXiv (Cornell University)
  73. Formal modeling of intrusion detection systems
    Lionel Nganyewou Tidjon · 2020 · theses.fr (ABES)
  74. Learning of Emergent Behaviors in Collective Virtual Robots using ANN and Genetic Algorithm
    Kyung-Dal Cho · 2004 · International Journal of Fuzzy Logic and Intelligent Systems
  75. Prediction in Dynamic Environment:Robocup Rescue Exploration
    Andy Song, Lin Padgham, Lawrence Cavendon · 2010
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  81. Adaptive Realities: Human-in-the-Loop AI for Trustworthy XR Training in Safety-Critical Domains
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  82. An RL-Enhanced Multi-Agent Framework for Scalable and Intelligent Business Intelligence Systems
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  83. BCI-Inspired Adaptive Agents in Human–Robot Interaction: A Structural Framework for Coordinated Interaction Design
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