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» Learning action effects in partially observable domains
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BC
2002
193views more  BC 2002»
14 years 9 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon
RSS
2007
176views Robotics» more  RSS 2007»
14 years 11 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...
IJCV
2010
574views more  IJCV 2010»
14 years 8 months ago
Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding
We propose a novel approach to understanding activities from their partial observations monitored through multiple non-overlapping cameras separated by unknown time gaps. In our...
Chen Change Loy, Tao Xiang, Shaogang Gong
EXPERT
2010
145views more  EXPERT 2010»
14 years 7 months ago
Interaction Analysis with a Bayesian Trajectory Model
Human behavior recognition is one of the most important and challenging objectives performed by intelligent vision systems. Several issues must be faced in this domain ranging fro...
Alessio Dore, Carlo S. Regazzoni
CSL
2010
Springer
14 years 9 months ago
Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
Blaise Thomson, Steve Young