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» Using Learned Policies in Heuristic-Search Planning
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2007
176views Robotics» more  RSS 2007»
13 years 6 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
GECCO
2005
Springer
152views Optimization» more  GECCO 2005»
13 years 10 months ago
GAMM: genetic algorithms with meta-models for vision
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
Greg Lee, Vadim Bulitko
IROS
2006
IEEE
165views Robotics» more  IROS 2006»
13 years 10 months ago
Learning Relational Navigation Policies
— Navigation is one of the fundamental tasks for a mobile robot. The majority of path planning approaches has been designed to entirely solve the given problem from scratch given...
Alexandru Cocora, Kristian Kersting, Christian Pla...
IJAMC
2008
93views more  IJAMC 2008»
13 years 4 months ago
Meaningful access: policy, management and orchestration
: Access management for learning communities requires a unified theory, sustaining the implementation of instructional policies, for `social networks'. The management method w...
Ioan Rosca, Val Rosca
AI
1999
Springer
13 years 4 months ago
Learning Action Strategies for Planning Domains
There are many different approaches to solving planning problems, one of which is the use of domain specific control knowledge to help guide a domain independent search algorithm. ...
Roni Khardon