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» Autonomous transfer for reinforcement learning
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82
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CORR
2010
Springer
152views Education» more  CORR 2010»
14 years 9 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
98
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CI
2005
106views more  CI 2005»
14 years 9 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird
ICRA
2009
IEEE
138views Robotics» more  ICRA 2009»
15 years 4 months ago
Which landmark is useful? Learning selection policies for navigation in unknown environments
Abstract— In general, a mobile robot that operates in unknown environments has to maintain a map and has to determine its own location given the map. This introduces significant...
Hauke Strasdat, Cyrill Stachniss, Wolfram Burgard
LAMAS
2005
Springer
15 years 3 months ago
An Overview of Cooperative and Competitive Multiagent Learning
Abstract Multi-agent systems (MASs) is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexiti...
Pieter Jan't Hoen, Karl Tuyls, Liviu Panait, Sean ...
ENTER
2009
Springer
15 years 4 months ago
Learning Adaptive Recommendation Strategies for Online Travel Planning
Conversational recommender systems support human-computer interaction strategies in order to assist online tourists in the important activity of dynamic packaging, i.e., in buildi...
Tariq Mahmood, Francesco Ricci, Adriano Venturini