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» Reinforcement Learning: An Introduction
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NIPS
1994
13 years 9 months ago
Generalization in Reinforcement Learning: Safely Approximating the Value Function
To appear in: G. Tesauro, D. S. Touretzky and T. K. Leen, eds., Advances in Neural Information Processing Systems 7, MIT Press, Cambridge MA, 1995. A straightforward approach to t...
Justin A. Boyan, Andrew W. Moore
JMLR
2010
125views more  JMLR 2010»
13 years 2 months ago
Variational methods for Reinforcement Learning
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Thomas Furmston, David Barber
ATAL
2006
Springer
13 years 12 months ago
Reinforcement learning for declarative optimization-based drama management
A long-standing challenge in interactive entertainment is the creation of story-based games with dynamically responsive story-lines. Such games are populated by multiple objects a...
Mark J. Nelson, David L. Roberts, Charles Lee Isbe...
FLAIRS
1998
13 years 9 months ago
Analytical Design of Reinforcement Learning Tasks
Reinforcement learning (RL) problems constitute an important class of learning and control problems faced by artificial intelligence systems. In these problems, one is faced with ...
Robert E. Smith
GECCO
2008
Springer
182views Optimization» more  GECCO 2008»
13 years 9 months ago
Scaling ant colony optimization with hierarchical reinforcement learning partitioning
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
Erik J. Dries, Gilbert L. Peterson