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» Gaussian Processes in Reinforcement Learning
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IJCAI
2007
14 years 11 months ago
Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning
TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD...
Ah-Hwee Tan
NIPS
2000
14 years 11 months ago
Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task
The problem of reinforcement learning in large factored Markov decision processes is explored. The Q-value of a state-action pair is approximated by the free energy of a product o...
Brian Sallans, Geoffrey E. Hinton
ICCBR
2009
Springer
15 years 4 months ago
Quality Enhancement Based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender
Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help use...
Maria Salamó, Sergio Escalera, Petia Radeva
EWCBR
2008
Springer
14 years 11 months ago
Recognizing the Enemy: Combining Reinforcement Learning with Strategy Selection Using Case-Based Reasoning
This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...
JMLR
2010
125views more  JMLR 2010»
14 years 4 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