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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
AIEDAM
1999
157views more  AIEDAM 1999»
13 years 7 months ago
Representing a robotic domain using temporal description logics
A temporal logic for representing and reasoning on a robotic domain is presented. Actions are represented by describing what is true while the action itself is occurring, and plan...
Alessandro Artale, Enrico Franconi
CVIU
2008
207views more  CVIU 2008»
13 years 7 months ago
A differential geometric approach to representing the human actions
This paper presents a novel representation for human actions which encodes the variations in the shape and motion of the performing actor. When an actor performs an action, at eac...
Alper Yilmaz, Mubarak Shah
ICDE
2006
IEEE
152views Database» more  ICDE 2006»
14 years 8 months ago
Mining Actionable Patterns by Role Models
Data mining promises to discover valid and potentially useful patterns in data. Often, discovered patterns are not useful to the user. "Actionability" addresses this pro...
Ke Wang, Yuelong Jiang, Alexander Tuzhilin
ICASSP
2010
IEEE
13 years 7 months ago
Action change detection in video by covariance matching of silhouette tunnels
Action recognition is an important but challenging problem in video analytics with a number of solutions proposed to date. However, even if a reliable model for action representat...
Kai Guo, Prakash Ishwar, Janusz Konrad