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TSMC
2008
146views more  TSMC 2008»
13 years 5 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
ATAL
2007
Springer
13 years 11 months ago
Reinforcement learning in extensive form games with incomplete information: the bargaining case study
We consider the problem of finding optimal strategies in infinite extensive form games with incomplete information that are repeatedly played. This problem is still open in lite...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Ni...
CLIMA
2007
13 years 6 months ago
EVOLP: Tranformation-Based Semantics
Over the years, Logic Programming has proved to be a good and natural tool for expressing, querying and manipulating explicit knowledge in many areas of computer science. However, ...
Martin Slota, João Leite
AAAI
2010
13 years 6 months ago
A General Game Description Language for Incomplete Information Games
A General Game Player is a system that can play previously unknown games given nothing but their rules. The Game Description Language (GDL) has been developed as a highlevel knowl...
Michael Thielscher
AAAI
2008
13 years 7 months ago
Perpetual Learning for Non-Cooperative Multiple Agents
This paper examines, by argument, the dynamics of sequences of behavioural choices made, when non-cooperative restricted-memory agents learn in partially observable stochastic gam...
Luke Dickens