Vidal's libraryTitle: | Multi-Agent Reinforcement Learning:a critical survey |
Author: | Yoav Shoham, Rob Powers, and Trond Grenager |
Year: | 2003 |
Abstract: | We survey the recent work in AI on multi-agent reinforcement learning (that is, learning in stochastic games). We then argue that, while exciting, this work is flawed. The fundamental flaw is unclarity about the problem or problems being addressed. After tracing a representative sample of the recent literature, we identify four well-defined problems in multi-agent reinforcement learning, single out the problem that in our view is most suitable for AI, and make some remarks about how we believe progress is to b e made on this problem. |
Cited by 34 - Google Scholar
@Unpublished{shoham03a,
author = {Yoav Shoham and Rob Powers and Trond Grenager},
title = {Multi-{A}gent Reinforcement Learning:a critical
survey},
note = {Unpublished survey},
year = 2003,
abstract = {We survey the recent work in AI on multi-agent
reinforcement learning (that is, learning in
stochastic games). We then argue that, while
exciting, this work is flawed. The fundamental flaw
is unclarity about the problem or problems being
addressed. After tracing a representative sample of
the recent literature, we identify four well-defined
problems in multi-agent reinforcement learning,
single out the problem that in our view is most
suitable for AI, and make some remarks about how we
believe progress is to b e made on this problem.},
keywords = {multiagent learning survey},
googleid = {4pMLvwoXnp8J:scholar.google.com/},
url = {http://jmvidal.cse.sc.edu/library/shoham03a.pdf},
cluster = {11501655833273144290}
}
Last modified: Wed Mar 9 10:16:03 EST 2011