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» An MDP Approach for Explanation Generation
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CORR
2012
Springer
235views Education» more  CORR 2012»
12 years 3 months ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
AIPS
2009
13 years 8 months ago
Navigation Planning in Probabilistic Roadmaps with Uncertainty
Probabilistic Roadmaps (PRM) are a commonly used class of algorithms for robot navigation tasks where obstacles are present in the environment. We examine the situation where the ...
Michael Kneebone, Richard Dearden
LCPC
2005
Springer
14 years 1 months ago
Analytic Models and Empirical Search: A Hybrid Approach to Code Optimization
Compilers employ system models, sometimes implicitly, to make code optimization decisions. These models are analytic; they reflect their implementor’s understanding and beliefs ...
Arkady Epshteyn, María Jesús Garzar&...
IBPRIA
2007
Springer
13 years 9 months ago
Automatic Learning of Conceptual Knowledge in Image Sequences for Human Behavior Interpretation
This work describes an approach for the interpretation and explanation of human behavior in image sequences, within the context of a Cognitive Vision System. The information source...
Pau Baiget, Carles Fernández Tena, F. Xavie...
TKDE
2008
123views more  TKDE 2008»
13 years 7 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko