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» On the Complexity of Exclusion Algorithms for Optimization
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CEC
2009
IEEE
16 years 4 days ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
15 years 12 months ago
Insight knowledge in search based software testing
Software testing can be re-formulated as a search problem, hence search algorithms (e.g., Genetic Algorithms) can be used to tackle it. Most of the research so far has been of emp...
Andrea Arcuri
IJCNN
2007
IEEE
15 years 11 months ago
Parallel Learning of Large Fuzzy Cognitive Maps
— Fuzzy Cognitive Maps (FCMs) are a class of discrete-time Artificial Neural Networks that are used to model dynamic systems. A recently introduced supervised learning method, wh...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
SASO
2007
IEEE
15 years 11 months ago
On Scaling Multi-Agent Task Reallocation Using Market-Based Approach
Multi-agent systems (MAS) provide a promising technology for addressing problems such as search and rescue missions, mine sweeping, and surveillance. These problems are a form of ...
Rajesh K. Karmani, Timo Latvala, Gul Agha
FSTTCS
2007
Springer
15 years 11 months ago
Solving Parity Games in Big Steps
Abstract. This paper proposes a new algorithm that improves the complexity bound for solving parity games. Our approach combines McNaughton’s iterated fixed point algorithm with...
Sven Schewe