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106
Voted
GECCO
2006
Springer
147views Optimization» more  GECCO 2006»
15 years 7 months ago
Redundant genes and the evolution of robustness
In this paper we demonstrate that pressure for robustness combined with function sets containing redundant genes can cause an evolutionary system to avoid a more fit solution in f...
Russell Thomason, Terence Soule
GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
15 years 7 months ago
Combining genetic algorithms with squeaky-wheel optimization
The AI optimization algorithm called "Squeaky-Wheel Optimization" (SWO) has proven very effective in a variety of real-world applications. Although the ideas behind SWO ...
Justin Terada, Hoa Vo, David Joslin
112
Voted
GECCO
2006
Springer
189views Optimization» more  GECCO 2006»
15 years 7 months ago
Game theory as a new paradigm for phenotype characterization of genetic algorithms
In this paper, it is presented a new way to characterize the phenotype in the context of Genetic Algorithms through the use of Game Theory as a theoretical foundation to define a ...
Otávio Noura Teixeira, Artur Noura Teixeira...
135
Voted
GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 7 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
129
Voted
GECCO
2006
Springer
164views Optimization» more  GECCO 2006»
15 years 7 months ago
Adaptation for parallel memetic algorithm based on population entropy
In this paper, we propose the island model parallel memetic algorithm with diversity-based dynamic adaptive strategy (PMADLS) for controlling the local search frequency and demons...
Jing Tang, Meng-Hiot Lim, Yew-Soon Ong