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SBIA
2004
Springer
14 years 23 days ago
Heuristically Accelerated Q-Learning: A New Approach to Speed Up Reinforcement Learning
This work presents a new algorithm, called Heuristically Accelerated Q–Learning (HAQL), that allows the use of heuristics to speed up the well-known Reinforcement Learning algori...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
ICMLA
2010
13 years 5 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...
ATAL
2008
Springer
13 years 9 months ago
Reinforcement learning for DEC-MDPs with changing action sets and partially ordered dependencies
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
Thomas Gabel, Martin A. Riedmiller
AAMAS
2007
Springer
13 years 7 months ago
Reaching pareto-optimality in prisoner's dilemma using conditional joint action learning
We consider a repeated Prisoner’s Dilemma game where two independent learning agents play against each other. We assume that the players can observe each others’ action but ar...
Dipyaman Banerjee, Sandip Sen
ESANN
2006
13 years 8 months ago
A multiagent architecture for concurrent reinforcement learning
In this paper we propose a multiagent architecture for implementing concurrent reinforcement learning, an approach where several agents, sharing the same environment, perceptions ...
Victor Uc Cetina