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AI
2002
Springer
15 years 6 months ago
Multiagent learning using a variable learning rate
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Michael H. Bowling, Manuela M. Veloso
SIGECOM
2011
ACM
249views ECommerce» more  SIGECOM 2011»
14 years 9 months ago
Leading dynamics to good behavior
: Many natural games can have a dramatic difference between the quality of their best and worst Nash equilibria, even in pure strategies. Yet, nearly all work to date on dynamics s...
Maria-Florina Balcan
IPPS
2005
IEEE
15 years 12 months ago
A Powerful Direct Mechanism for Optimal WWW Content Replication
This paper addresses the problem of fine-grained data replication in large distributed systems, such as the Internet, so as to minimize the user access delays. With fine-grained d...
Samee Ullah Khan, Ishfaq Ahmad
ATAL
2003
Springer
15 years 11 months ago
A selection-mutation model for q-learning in multi-agent systems
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
Karl Tuyls, Katja Verbeeck, Tom Lenaerts
NIPS
2007
15 years 7 months ago
Computing Robust Counter-Strategies
Adaptation to other initially unknown agents often requires computing an effective counter-strategy. In the Bayesian paradigm, one must find a good counterstrategy to the inferre...
Michael Johanson, Martin Zinkevich, Michael H. Bow...