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» A strategy for selecting multiple components
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CEC
2005
IEEE
13 years 11 months ago
Evolution and prioritization of survival strategies for a simulated robot in Xpilot
Simulated evolution by the use of Genetic Algorithms (GA) is presented as the solution to a twofaceted problem: the challenge for an autonomous agent to learn the reactive componen...
Gary B. Parker, Timothy S. Doherty, Matt Parker
EOR
2008
88views more  EOR 2008»
13 years 9 months ago
Selection of a correlated equilibrium in Markov stopping games
This paper deals with an extension of the concept of correlated strategies to Markov stopping games. The Nash equilibrium approach to solving nonzero-sum stopping games may give m...
David M. Ramsey, Krzysztof Szajowski
MCS
2009
Springer
14 years 3 months ago
Selective Ensemble under Regularization Framework
An ensemble is generated by training multiple component learners for a same task and then combining them for predictions. It is known that when lots of trained learners are availab...
Nan Li, Zhi-Hua Zhou
ETS
2007
IEEE
128views Hardware» more  ETS 2007»
13 years 10 months ago
Selecting Power-Optimal SBST Routines for On-Line Processor Testing
Software-Based Self-Test (SBST) has emerged as an effective strategy for on-line testing of processors integrated in non-safety critical embedded system applications. Among the mo...
Andreas Merentitis, Nektarios Kranitis, Antonis M....
FLAIRS
2004
13 years 10 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber