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» Coordinating Multiple Agents via Reinforcement Learning
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ICML
1994
IEEE
15 years 1 months ago
Markov Games as a Framework for Multi-Agent Reinforcement Learning
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
Michael L. Littman
124
Voted

Publication
154views
13 years 12 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
ATAL
2007
Springer
15 years 3 months ago
Transfer via inter-task mappings in policy search reinforcement learning
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
83
Voted
HIS
2004
14 years 11 months ago
Stigmergy in Multi Agent Reinforcement Learning
In this paper, we describe how certain aspects of the biological phenomena of stigmergy can be imported into multiagent reinforcement learning (MARL), with the purpose of better e...
Raghav Aras, Alain Dutech, François Charpil...
AI
2004
Springer
15 years 2 months ago
Multi-attribute Decision Making in a Complex Multiagent Environment Using Reinforcement Learning with Selective Perception
Abstract. Choosing between multiple alternative tasks is a hard problem for agents evolving in an uncertain real-time multiagent environment. An example of such environment is the ...
Sébastien Paquet, Nicolas Bernier, Brahim C...