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» Predicting Opponent Actions by Observation
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ICML
2006
IEEE
14 years 8 months ago
Predictive linear-Gaussian models of controlled stochastic dynamical systems
We introduce the controlled predictive linearGaussian model (cPLG), a model that uses predictive state to model discrete-time dynamical systems with real-valued observations and v...
Matthew R. Rudary, Satinder P. Singh
AAAI
2012
11 years 10 months ago
An Object-Based Bayesian Framework for Top-Down Visual Attention
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Ali Borji, Dicky N. Sihite, Laurent Itti
ECCV
2004
Springer
14 years 9 months ago
Decision Theoretic Modeling of Human Facial Displays
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
Jesse Hoey, James J. Little
ICML
2004
IEEE
14 years 8 months ago
Utile distinction hidden Markov models
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
Daan Wierstra, Marco Wiering
ECP
1997
Springer
105views Robotics» more  ECP 1997»
14 years 23 hour ago
Planning, Learning, and Executing in Autonomous Systems
Systems that act autonomously in the environment have to be able to integrate three basic behaviors: planning, execution, and learning. Planning involves describing a set of action...
Ramón García-Martínez, Daniel...