Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems
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Published By Springer Berlin Heidelberg

9783540609230, 9783540497264

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Learn your opponent's strategy (in polynomial time)!

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_26 ◽

1996 ◽

pp. 164-176 ◽

Cited By ~ 5

Author(s):

Yishay Mor ◽

Claudia V. Goldman ◽

Jeffrey S. Rosenschein

Keyword(s):

Polynomial Time

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Refinement in agent groups

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_17 ◽

1996 ◽

pp. 22-39 ◽

Cited By ~ 3

Author(s):

Ciara Byrne ◽

Peter Edwards

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Using reciprocity to adapt to others

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_29 ◽

1996 ◽

pp. 206-217 ◽

Cited By ~ 4

Author(s):

Sandip Sen ◽

Mahendra Sekaran

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Learning to reduce communication cost on task negotiation among multiple autonomous mobile robots

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_27 ◽

1996 ◽

pp. 177-190 ◽

Cited By ~ 6

Author(s):

Takuya Ohko ◽

Kazuo Hiraki ◽

Yuichiro Anzai

Keyword(s):

Mobile Robots ◽

Communication Cost ◽

Autonomous Mobile Robots

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A multi-agent environment for department of defense distribution

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_19 ◽

1996 ◽

pp. 53-84

Author(s):

Laurence Glicoes ◽

Richard Staats ◽

Michael Huhns

Keyword(s):

Department Of Defense ◽

Multi Agent

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Learning in multi-robot systems

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_25 ◽

1996 ◽

pp. 152-163 ◽

Cited By ~ 16

Author(s):

Maja J. Matarić

Keyword(s):

Robot Systems ◽

Multi Robot

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On multiagent Q-learning in a semi-competitive domain

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_28 ◽

1996 ◽

pp. 191-205 ◽

Cited By ~ 20

Author(s):

Tuomas W. Sandholm ◽

Robert H. Crites

Keyword(s):

Q Learning

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Evolving behavioral strategies in predators and prey

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_22 ◽

1996 ◽

pp. 113-126 ◽

Cited By ~ 52

Author(s):

Thomas Haynes ◽

Sandip Sen

Keyword(s):

Behavioral Strategies

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Mutually supervised learning in multiagent systems

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_20 ◽

1996 ◽

pp. 85-96 ◽

Cited By ~ 6

Author(s):

Claudia V. Goldman ◽

Jeffrey S. Rosenschein

Keyword(s):

Supervised Learning ◽

Multiagent Systems

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Opponent modeling in multi-agent systems

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems ◽

10.1007/3-540-60923-7_18 ◽

1996 ◽

pp. 40-52 ◽

Cited By ~ 20

Author(s):

David Carmel ◽

Shaul Markovitch

Keyword(s):

Multi Agent Systems ◽

Agent Systems ◽

Opponent Modeling ◽

Multi Agent

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Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent SystemsLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Learn your opponent's strategy (in polynomial time)!

Refinement in agent groups

Using reciprocity to adapt to others

Learning to reduce communication cost on task negotiation among multiple autonomous mobile robots

A multi-agent environment for department of defense distribution

Learning in multi-robot systems

On multiagent Q-learning in a semi-competitive domain

Evolving behavioral strategies in predators and prey

Mutually supervised learning in multiagent systems

Opponent modeling in multi-agent systems

Lecture Notes in Computer Science - Adaption and Learning in Multi-Agent Systems
Latest Publications