Paper Info
Title
Comparing evolutionary computation techniques via their representation
Abstract
In the current paper a rigorous mathematical language for comparing evolutionary computation techniques via their representation is developed. A binary semi-genetic algorithm is introduced, and it is proved that in a certain sense any reasonable evolutionary search algorithm can be re-encoded by a binary semi-genetic algorithm (see corollaries 15 and 16). Moreover, an explicit bijection between the set of all such re-encodings and the collection of certain n-tuples of invariant subsets is constructed (see theorem 14). Finally, all possible re-encodings of a given heuristic search algorithm by a classical genetic algorithm are entirely classified in terms of invariant subsets of the search space in connection with Radcliffe's forma (see [9] and theorem 20).
Year
Venue
Keywords
2003
GECCO
evolutionary computation technique,classical genetic algorithm,certain n-tuples,certain sense,search space,binary semi-genetic algorithm,invariant subsets,possible re-encodings,heuristic search algorithm,reasonable evolutionary search algorithm,evolutionary computing,genetic algorithm,heuristic search
Field
DocType
Volume
Search algorithm,Evolutionary algorithm,Human-based evolutionary computation,Computer science,Artificial intelligence,Evolutionary programming,Interactive evolutionary computation,Discrete mathematics,Mathematical optimization,Genetic representation,Cultural algorithm,Best-first search,Machine learning
Conference
2723
ISSN
ISBN
Citations 
0302-9743
3-540-40602-6
7
PageRank 
References 
Authors
0.62
10
1
Name
Order
Citations
PageRank
Boris Mitavskiy110911.06