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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
ICC
2007
IEEE
148views Communications» more  ICC 2007»
14 years 2 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...
ATAL
2007
Springer
14 years 2 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
CIMCA
2006
IEEE
14 years 1 months ago
Model-driven Walks for Resource Discovery in Peer-to-Peer Networks
In this paper, a distributed and adaptive approach for resource discovery in peer-to-peer networks is presented. This approach is based on the mobile agent paradigm and the random...
Mohamed Bakhouya, Jaafar Gaber
NN
2007
Springer
105views Neural Networks» more  NN 2007»
13 years 7 months ago
Guiding exploration by pre-existing knowledge without modifying reward
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
Kary Främling