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JMLR
2010
125views more  JMLR 2010»
14 years 10 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
15 years 7 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...
GECCO
2008
Springer
182views Optimization» more  GECCO 2008»
15 years 4 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
148
Voted
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...
119
Voted
ATAL
2007
Springer
15 years 9 months ago
Theoretical advantages of lenient Q-learners: an evolutionary game theoretic perspective
This paper presents the dynamics of multiple reinforcement learning agents from an Evolutionary Game Theoretic (EGT) perspective. We provide a Replicator Dynamics model for tradit...
Liviu Panait, Karl Tuyls