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» Reinforcement learning with Gaussian processes
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92
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SBIA
2004
Springer
15 years 7 months ago
Heuristically Accelerated Q-Learning: A New Approach to Speed Up Reinforcement Learning
This work presents a new algorithm, called Heuristically Accelerated Q–Learning (HAQL), that allows the use of heuristics to speed up the well-known Reinforcement Learning algori...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
15 years 8 months ago
Considering Unseen States as Impossible in Factored Reinforcement Learning
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...
JDCTA
2010
160views more  JDCTA 2010»
14 years 8 months ago
Learning and Decision Making in Human During a Game of Matching Pennies
To gain insights into the neural basis of such adaptive decision-making processes, we investigated the nature of learning process in humans playing a competitive game with binary ...
Jianfeng Hu, Xiaofeng Li, Jinghai Yin
107
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IJCAI
2003
15 years 3 months ago
Multiple-Goal Reinforcement Learning with Modular Sarsa(0)
We present a new algorithm, GM-Sarsa(0), for finding approximate solutions to multiple-goal reinforcement learning problems that are modeled as composite Markov decision processe...
Nathan Sprague, Dana H. Ballard
96
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FLAIRS
1998
15 years 3 months ago
Optimizing Production Manufacturing Using Reinforcement Learning
Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
Sridhar Mahadevan, Georgios Theocharous