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ATAL
2008
Springer
13 years 9 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
ICML
2010
IEEE
13 years 5 months ago
Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda
Temporal difference (TD) algorithms are attractive for reinforcement learning due to their ease-of-implementation and use of "bootstrapped" return estimates to make effi...
Carlton Downey, Scott Sanner
AIIDE
2009
13 years 8 months ago
Learning Character Behaviors Using Agent Modeling in Games
Our goal is to provide learning mechanisms to game agents so they are capable of adapting to new behaviors based on the actions of other agents. We introduce a new on-line reinfor...
Richard Zhao, Duane Szafron
ATAL
2005
Springer
14 years 1 months ago
Modeling task allocation using a decision theoretic model
Mediation is the process of decomposing a task into subtasks, finding agents suitable for these subtasks and negotiating with agents to obtain commitments to execute these subtas...
Sherief Abdallah, Victor R. Lesser
CVPR
2009
IEEE
1133views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Hierarchical Spatio-Temporal Context Modeling for Action Recognition
The problem of recognizing actions in realistic videos is challenging yet absorbing owing to its great potentials in many practical applications. Most previous research is limit...
Jintao Li, Ju Sun, Loong Fah Cheong, Shuicheng Yan...