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2007
176views Robotics» more  RSS 2007»
13 years 8 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...
AAAI
1998
13 years 8 months ago
Learning Investment Functions for Controlling the Utility of Control Knowledge
The utility problem occurs when the cost of the acquired knowledge outweighs its bene ts. When the learner acquires control knowledge for speeding up a problem solver, the bene t ...
Oleg Ledeniov, Shaul Markovitch
AAI
2005
117views more  AAI 2005»
13 years 7 months ago
Machine Learning in Hybrid Hierarchical and Partial-Order Planners for Manufacturing Domains
The application of AI planning techniques to manufacturing systems is being widely deployed for all the tasks involved in the process, from product design to production planning an...
Susana Fernández, Ricardo Aler, Daniel Borr...
HICSS
2005
IEEE
120views Biometrics» more  HICSS 2005»
14 years 1 months ago
Learning from Project Experiences Using a Legacy-Based Approach
As project teams become used more widely, the question of how to capitalize on the knowledge learned in these teams remains an open issue. Using previous research on transactive m...
Lynne P. Cooper, Ann Majchrzak, Samer Faraj
AIPS
1994
13 years 8 months ago
Robot Motion Planning Integrating Planning Strategies and Learning Methods
Robot motion planning in a dynamic cluttered workspace requires the capability of dealing with obstacles and deadlock situations. The paper analyzes situations where the robot is ...
Luca Maria Gambardella, Cristina Versino