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» Approximate Learning of Dynamic Models
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HICSS
2003
IEEE
116views Biometrics» more  HICSS 2003»
15 years 10 months ago
Modeling Instrumental Conditioning - The Behavioral Regulation Approach
Basically, instrumental conditioning is learning through consequences: Behavior that produces positive results (high “instrumental response”) is reinforced, and that which pro...
Jose J. Gonzalez, Agata Sawicka
KES
2005
Springer
15 years 10 months ago
Learning Within the BDI Framework: An Empirical Analysis
One of the limitations of the BDI (Belief-Desire-Intention) model is the lack of any explicit mechanisms within the architecture to be able to learn. In particular, BDI agents do n...
Toan Phung, Michael Winikoff, Lin Padgham
NIPS
1993
15 years 6 months ago
Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming
Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have ...
Christopher G. Atkeson
ECCV
2004
Springer
16 years 6 months ago
A Statistical Model for General Contextual Object Recognition
We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
Peter Carbonetto, Nando de Freitas, Kobus Barnard
PASTE
2010
ACM
15 years 10 months ago
Learning universal probabilistic models for fault localization
Recently there has been significant interest in employing probabilistic techniques for fault localization. Using dynamic dependence information for multiple passing runs, learnin...
Min Feng, Rajiv Gupta