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JACIII
2007
105views more  JACIII 2007»
14 years 9 months ago
Reinforcement Learning for Penalty Avoidance in Continuous State Spaces
Kazuteru Miyazaki, Shigenobu Kobayashi
ACMICEC
2008
ACM
272views ECommerce» more  ACMICEC 2008»
14 years 11 months ago
Adapting the interaction state model in conversational recommender systems
Conventional conversational recommender systems support interaction strategies that are hard-coded into the system in advance. In this context, Reinforcement Learning techniques h...
Tariq Mahmood, Francesco Ricci
ROBOCUP
2000
Springer
130views Robotics» more  ROBOCUP 2000»
15 years 1 months ago
Improvement Continuous Valued Q-learning and Its Application to Vision Guided Behavior Acquisition
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
Yasutake Takahashi, Masanori Takeda, Minoru Asada
ICRA
2010
IEEE
143views Robotics» more  ICRA 2010»
14 years 8 months ago
Apprenticeship learning via soft local homomorphisms
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
Abdeslam Boularias, Brahim Chaib-draa
COLT
2008
Springer
14 years 11 months ago
Adaptive Aggregation for Reinforcement Learning with Efficient Exploration: Deterministic Domains
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Andrey Bernstein, Nahum Shimkin