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103
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CEC
2005
IEEE
15 years 6 months ago
Complexity transitions in evolutionary algorithms: evaluating the impact of the initial population
Abstract- This paper proposes an evolutionary approach for the composition of solutions in an incremental way. The approach is based on the metaphor of transitions in complexity di...
Anne Defaweux, Tom Lenaerts, Jano I. van Hemert, J...
104
Voted
ICML
1998
IEEE
16 years 1 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
87
Voted
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
15 years 6 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
117
Voted
GECCO
2003
Springer
148views Optimization» more  GECCO 2003»
15 years 5 months ago
Structural and Functional Sequence Test of Dynamic and State-Based Software with Evolutionary Algorithms
Evolutionary Testing (ET) has been shown to be very successful for testing real world applications [10]. The original ET approach focusesonsearching for a high coverage of the test...
André Baresel, Hartmut Pohlheim, Sadegh Sad...
95
Voted
GECCO
2008
Springer
139views Optimization» more  GECCO 2008»
15 years 1 months ago
Evolutionary design of dynamic SwarmScapes
This paper discusses interactive evolutionary algorithms and their application in swarm-based image generation. From an artist’s perspective, the computer-generated patterns oï¬...
Namrata Khemka, Scott Novakowski, Gerald Hushlak, ...