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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 3 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
13 years 11 months ago
Experimental analysis of binary differential evolution in dynamic environments
Many real-world optimization problems are dynamic in nature. The interest in the Evolutionary Algorithms (EAs) community in applying EA variants to dynamic optimization problems h...
Alp Emre Kanlikilicer, Ali Keles, Sima Uyar
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
13 years 10 months ago
Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments
This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the perf...
Kagan Tumer, Adrian K. Agogino
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
13 years 6 months ago
Optinformatics for schema analysis of binary genetic algorithms
Given the importance of optimization and informatics which are the two broad fields of research, we present an instance of Optinformatics which denotes the specialization of info...
Minh Nghia Le, Yew-Soon Ong, Quang Huy Nguyen 0001
WSC
2000
13 years 6 months ago
Cost/benefit analysis of interval jumping in power-control simulation
Computation of power control calculations is one of the most time-consuming aspects of simulating wireless communication systems. These calculations are critical to understanding ...
David M. Nicol, L. Felipe Perrone