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ATAL
2009
Springer
15 years 4 months ago
Multiagent reinforcement learning: algorithm converging to Nash equilibrium in general-sum discounted stochastic games
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Natalia Akchurina
AI
2001
Springer
15 years 2 months ago
Imitation and Reinforcement Learning in Agents with Heterogeneous Actions
Reinforcement learning techniques are increasingly being used to solve di cult problems in control and combinatorial optimization with promising results. Implicit imitation can acc...
Bob Price, Craig Boutilier
ICML
2004
IEEE
15 years 10 months ago
Dynamic abstraction in reinforcement learning via clustering
Abstraction in Reinforcement Learning via Clustering Shie Mannor shie@mit.edu Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA ...
Shie Mannor, Ishai Menache, Amit Hoze, Uri Klein
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ICML
2002
IEEE
15 years 10 months ago
Discovering Hierarchy in Reinforcement Learning with HEXQ
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...
Bernhard Hengst
ECML
2004
Springer
15 years 3 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner