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NIPS
2004
14 years 12 months ago
Intrinsically Motivated Reinforcement Learning
Psychologists call behavior intrinsically motivated when it is engaged in for its own sake rather than as a step toward solving a specific problem of clear practical value. But wh...
Satinder P. Singh, Andrew G. Barto, Nuttapong Chen...
NIPS
2000
14 years 12 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
ICANN
2010
Springer
14 years 11 months ago
Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
Frank-Florian Steege, André Hartmann, Erik ...
IAT
2008
IEEE
14 years 10 months ago
Cognitive Agents Integrating Rules and Reinforcement Learning for Context-Aware Decision Support
While context-awareness has been found to be effective for decision support in complex domains, most of such decision support systems are hard-coded, incurring significant develop...
Teck-Hou Teng, Ah-Hwee Tan
CONSTRAINTS
2008
89views more  CONSTRAINTS 2008»
14 years 10 months ago
A Reinforcement Learning Approach to Interval Constraint Propagation
When solving systems of nonlinear equations with interval constraint methods, it has often been observed that many calls to contracting operators do not participate actively to th...
Frédéric Goualard, Christophe Jerman...