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IDEAL
2004
Springer
14 years 3 months ago
Learning Users' Interests in a Market-Based Recommender System
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings
IJCNN
2006
IEEE
14 years 3 months ago
Global Reinforcement Learning in Neural Networks with Stochastic Synapses
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
Xiaolong Ma, Konstantin Likharev
ILP
2000
Springer
14 years 1 months ago
Using ILP to Improve Planning in Hierarchical Reinforcement Learning
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
Mark D. Reid, Malcolm R. K. Ryan
WSC
2007
14 years 5 days ago
Optimizing time warp simulation with reinforcement learning techniques
Adaptive Time Warp protocols in the literature are usually based on a pre-defined analytic model of the system, expressed as a closed form function that maps system state to cont...
Jun Wang, Carl Tropper
ICRA
2006
IEEE
124views Robotics» more  ICRA 2006»
14 years 3 months ago
Mobile Robot Programming in Education
— The Mobile Robot Programming Laboratory course has been taught at Carnegie Mellon University for the past twelve years. It is a problem-driven class designed for students with ...
Jean-François Lalonde, Christopher P. Bartl...