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» A strategy for selecting multiple components
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CEC
2005
IEEE
15 years 8 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»
15 years 6 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
16 years 1 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»
15 years 8 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
15 years 8 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