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ICML
1998
IEEE
16 years 6 months ago
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
Junling Hu, Michael P. Wellman
JUCS
2008
104views more  JUCS 2008»
15 years 5 months ago
Optimal Transit Price Negotiation: The Distributed Learning Perspective
: We present a distributed learning algorithm for optimizing transit prices in the inter-domain routing framework. We present a combined game theoretical and distributed algorithmi...
Dominique Barth, Loubna Echabbi, Chahinez Hamlaoui
AMAI
2006
Springer
15 years 6 months ago
Bargaining over multiple issues in finite horizon alternating-offers protocol
In this paper we study multi issue alternating-offers bargaining in a perfect information finite horizon setting, we determine the pertinent subgame perfect equilibrium, and we pro...
Francesco Di Giunta, Nicola Gatti
LAMAS
2005
Springer
15 years 11 months ago
Unifying Convergence and No-Regret in Multiagent Learning
We present a new multiagent learning algorithm, RVσ(t), that builds on an earlier version, ReDVaLeR . ReDVaLeR could guarantee (a) convergence to best response against stationary ...
Bikramjit Banerjee, Jing Peng
NIPS
2001
15 years 7 months ago
Playing is believing: The role of beliefs in multi-agent learning
We propose a new classification for multi-agent learning algorithms, with each league of players characterized by both their possible strategies and possible beliefs. Using this c...
Yu-Han Chang, Leslie Pack Kaelbling