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ESANN
2008
15 years 4 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
15 years 4 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»
14 years 9 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
122
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ATAL
2006
Springer
15 years 6 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...
ICC
2007
IEEE
148views Communications» more  ICC 2007»
15 years 9 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...