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» An MDP Approach for Explanation Generation
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2007
136views Robotics» more  RSS 2007»
13 years 9 months ago
The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
Ron Alterovitz, Thierry Siméon, Kenneth Y. ...
SIGIR
2012
ACM
11 years 10 months ago
Explanatory semantic relatedness and explicit spatialization for exploratory search
Exploratory search, in which a user investigates complex concepts, is cumbersome with today’s search engines. We present a new exploratory search approach that generates interac...
Brent Hecht, Samuel Carton, Mahmood Quaderi, Johan...
IJCAI
2007
13 years 9 months ago
Transferring Learned Control-Knowledge between Planners
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently guide the problem-space exploration. Machine learning (ML) provides several tec...
Susana Fernández, Ricardo Aler, Daniel Borr...
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...
JMLR
2006
120views more  JMLR 2006»
13 years 7 months ago
Learning Parts-Based Representations of Data
Many perceptual models and theories hinge on treating objects as a collection of constituent parts. When applying these approaches to data, a fundamental problem arises: how can w...
David A. Ross, Richard S. Zemel