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» Time-Extended Policies in Multi-Agent Reinforcement Learning
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ATAL
2004
Springer
9 years 3 months ago
Time-Extended Policies in Multi-Agent Reinforcement Learning
Many algorithms such as Q-learning successfully address reinforcement learning in single-agent multi-time-step problems. In addition there are methods that address reinforcement l...
Kagan Tumer, Adrian K. Agogino
AAAI
2010
8 years 11 months ago
Bayesian Policy Search for Multi-Agent Role Discovery
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Aaron Wilson, Alan Fern, Prasad Tadepalli
AAAI
2011
7 years 10 months ago
Coordinated Multi-Agent Reinforcement Learning in Networked Distributed POMDPs
In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND...
Chongjie Zhang, Victor R. Lesser
ICML
1994
IEEE
9 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
IAT
2005
IEEE
9 years 3 months ago
Self-Organizing Cognitive Agents and Reinforcement Learning in Multi-Agent Environment
This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
Ah-Hwee Tan, Dan Xiao
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