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ESANN
2008
13 years 10 months ago
Multilayer Perceptrons with Radial Basis Functions as Value Functions in Reinforcement Learning
Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibilit...
Victor Uc Cetina
NIPS
1994
13 years 10 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 3 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
14 years 21 days 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...
ICC
2007
IEEE
148views Communications» more  ICC 2007»
14 years 3 months ago
Improved Revenue and Radio Resource Usage through Inter-Operator Joint Radio Resource Management
— This paper proposes a two-layer Joint Radio Resource Management (JRRM) framework to improve the efficiency in multi-radio and multi-operator cellular scenarios. On the one hand...
Lorenza Giupponi, Ramón Agustí, Jord...