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CEC
2007
IEEE
16 years 28 days ago
Plateaus can be harder in multi-objective optimization
—In recent years a lot of progress has been made in understanding the behavior of evolutionary computation methods for single- and multi-objective problems. Our aim is to analyze...
Tobias Friedrich, Nils Hebbinghaus, Frank Neumann
GECCO
2005
Springer
128views Optimization» more  GECCO 2005»
16 years 2 days ago
Collaborative interactive evolution
Interactive evolutionary computation (IEC) has proven useful in a variety of applications by combining the subjective evaluation of a user with the massive parallel search power o...
Sean R. Szumlanski, Annie S. Wu, Charles E. Hughes
AAAI
2006
15 years 8 months ago
Conflict Resolution and a Framework for Collaborative Interactive Evolution
Interactive evolutionary computation (IEC) has proven useful in a variety of applications by combining the subjective evaluation of a user with the massive parallel search power o...
Sean R. Szumlanski, Annie S. Wu, Charles E. Hughes
GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
16 years 22 days ago
Genetically programmed learning classifier system description and results
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
Gregory Anthony Harrison, Eric W. Worden
ATAL
2005
Springer
16 years 3 days ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson