Adaption and Learning in Multi-Agent Systems IJCAI'95 Workshop Montréal, Canada, August 21, 1995 Proceedings / [electronic resource] :
edited by Gerhard Weiß, Sandip Sen.
- Berlin, Heidelberg : Springer Berlin Heidelberg, 1996.
- XII, 568 p. online resource.
- Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 1042 0302-9743 ; .
- Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 1042 .
Adaptation and learning in multi-agent systems: Some remarks and a bibliography -- Refinement in agent groups -- Opponent modeling in multi-agent systems -- A multi-agent environment for department of defense distribution -- Mutually supervised learning in multiagent systems -- A framework for distributed reinforcement learning -- Evolving behavioral strategies in predators and prey -- To learn or not to learn ...... -- A user-adaptive interface agency for interaction with a virtual environment -- Learning in multi-robot systems -- Learn your opponent's strategy (in polynomial time)! -- Learning to reduce communication cost on task negotiation among multiple autonomous mobile robots -- On multiagent Q-learning in a semi-competitive domain -- Using reciprocity to adapt to others -- Multiagent coordination with learning classifier systems.
This book is based on the workshop on Adaptation and Learning in Multi-Agent Systems, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. The 14 thoroughly reviewed revised papers reflect the whole scope of current aspects in the field: they describe and analyze, both experimentally and theoretically, new learning and adaption approaches for situations in which several agents have to cooperate or compete. Also included, and aimed at the novice reader, are a comprehensive introductory survey on the area with 154 references listed and a subject index. As the first book solely devoted to this area, this volume documents the state of the art and is thus indispensable for anyone active or interested in the field.
9783540497264
10.1007/3-540-60923-7 doi
Computer science.
Artificial intelligence.
Computer simulation.
Computer Science.
Artificial Intelligence (incl. Robotics).
Programming Languages, Compilers, Interpreters.
Simulation and Modeling.
Q334-342 TJ210.2-211.495
006.3
Adaptation and learning in multi-agent systems: Some remarks and a bibliography -- Refinement in agent groups -- Opponent modeling in multi-agent systems -- A multi-agent environment for department of defense distribution -- Mutually supervised learning in multiagent systems -- A framework for distributed reinforcement learning -- Evolving behavioral strategies in predators and prey -- To learn or not to learn ...... -- A user-adaptive interface agency for interaction with a virtual environment -- Learning in multi-robot systems -- Learn your opponent's strategy (in polynomial time)! -- Learning to reduce communication cost on task negotiation among multiple autonomous mobile robots -- On multiagent Q-learning in a semi-competitive domain -- Using reciprocity to adapt to others -- Multiagent coordination with learning classifier systems.
This book is based on the workshop on Adaptation and Learning in Multi-Agent Systems, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. The 14 thoroughly reviewed revised papers reflect the whole scope of current aspects in the field: they describe and analyze, both experimentally and theoretically, new learning and adaption approaches for situations in which several agents have to cooperate or compete. Also included, and aimed at the novice reader, are a comprehensive introductory survey on the area with 154 references listed and a subject index. As the first book solely devoted to this area, this volume documents the state of the art and is thus indispensable for anyone active or interested in the field.
9783540497264
10.1007/3-540-60923-7 doi
Computer science.
Artificial intelligence.
Computer simulation.
Computer Science.
Artificial Intelligence (incl. Robotics).
Programming Languages, Compilers, Interpreters.
Simulation and Modeling.
Q334-342 TJ210.2-211.495
006.3