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IROS
2007
IEEE
123views Robotics» more  IROS 2007»
14 years 1 months ago
Reinforcement learning in multi-dimensional state-action space using random rectangular coarse coding and Gibbs sampling
: This paper presents a coarse coding technique and an action selection scheme for reinforcement learning (RL) in multi-dimensional and continuous state-action spaces following con...
Kimura Kimura
IJCAI
2003
13 years 8 months ago
Action Selection for Single- and Multi-Robot Tasks Using Cooperative Extended Kohonen Maps
This paper presents an action selection framework based on an assemblage of self-organizing neural networks called Cooperative Extended Kohonen Maps. This framework encapsulates t...
Kian Hsiang Low, Wee Kheng Leow, Marcelo H. Ang Jr...
PAMI
2011
13 years 2 months ago
Action Recognition Using Mined Hierarchical Compound Features
—The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single frame object recogn...
Andrew Gilbert, John Illingworth, Richard Bowden
BC
2010
163views more  BC 2010»
13 years 4 months ago
Action and behavior: a free-energy formulation
We have previously tried to explain perceptual inference and learning under a free-energy principle that pursues Helmholtz's agenda to understand the brain in terms of energy ...
Karl J. Friston, Jean Daunizeau, James Kilner, Ste...
DAGM
2004
Springer
14 years 14 days ago
Multi-step Entropy Based Sensor Control for Visual Object Tracking
We describe a method for selecting optimal actions affecting the sensors in a probabilistic state estimation framework, with an application in selecting optimal zoom levels for a ...
Benjamin Deutsch, Matthias Zobel, Joachim Denzler,...