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» Reinforcement Learning with Hierarchies of Machines
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LAMAS
2005
Springer
15 years 11 months ago
Multi-agent Relational Reinforcement Learning
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
ICML
2007
IEEE
16 years 6 months ago
Cross-domain transfer for reinforcement learning
A typical goal for transfer learning algorithms is to utilize knowledge gained in a source task to learn a target task faster. Recently introduced transfer methods in reinforcemen...
Matthew E. Taylor, Peter Stone

Book
392views
17 years 4 months ago
Reinforcement Learning: An Introduction
"Reinforcement learning is learning what to do how to map situations to actions so as to maximize a numerical reward signal. The learner is not told which actions to take, as ...
Richard S. Sutton, Andrew G. Barto
PRICAI
2000
Springer
15 years 9 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
ICML
2004
IEEE
16 years 6 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