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PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 5 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
CONNECTION
2010
144views more  CONNECTION 2010»
15 years 4 months ago
The roles of the amygdala in the affective regulation of body, brain, and behaviour
Abstract. Despite the great amount of knowledge produced by the neuroscientific literature affective phenomena, current models tackling noncognitive aspects of behavior are often b...
Marco Mirolli, Francesco Mannella, Gianluca Baldas...
AAMAS
2005
Springer
15 years 6 months ago
Learning and Exploiting Relative Weaknesses of Opponent Agents
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
Shaul Markovitch, Ronit Reger
ENTCS
2006
176views more  ENTCS 2006»
15 years 6 months ago
Gauss: A Framework for Verifying Scientific Computing Software
High performance scientific computing software is of critical international importance as it supports scientific explorations and engineering. Software development in this area is...
Robert Palmer, Steve Barrus, Yu Yang, Ganesh Gopal...
AAAI
2007
15 years 8 months ago
Optimizing Anthrax Outbreak Detection Using Reinforcement Learning
The potentially catastrophic impact of a bioterrorist attack makes developing effective detection methods essential for public health. In the case of anthrax attack, a delay of ho...
Masoumeh T. Izadi, David L. Buckeridge