Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
Evaluating evolutionary algorithms
Artificial Intelligence - Special volume on empirical methods
Efficient generation of the binary reflected gray code and its applications
Communications of the ACM
Building Better Test Functions
Proceedings of the 6th International Conference on Genetic Algorithms
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Representation, search and genetic algorithms
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Proceedings of the 8th annual conference on Genetic and evolutionary computation
On the application of linear transformations for genetic algorithms optimization
International Journal of Knowledge-based and Intelligent Engineering Systems
Precision, local search and unimodal functions
Proceedings of the 10th annual conference on Genetic and evolutionary computation
IEEE Transactions on Evolutionary Computation
Implicit elitism in genetic search
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Evolving numerical constants in grammatical evolution with the ephemeral constant method
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Gray, binary and real valued encodings: quad search and locality proofs
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Hi-index | 0.03 |
Representations are formalized as encodings that map the search space to the vertex set of a graph. We define the notion of bit equivalent encodings and show that for such encodings the corresponding Walsh coefficients are also conserved. We focus on Gray codes as particular types of encoding and present a review of properties related to the use of Gray codes. Gray codes are widely used in conjunction with genetic algorithms and bit-climbing algorithms for parameter optimization problems. We present new convergence proofs for a special class of unimodal functions; the proofs show that a steepest ascent bit climber using any reflected Gray code representation reaches the global optimum in a number of steps that is linear with respect to the encoding size. There are in fact many different Gray codes. Shifting is defined as a mechanism for dynamically switching from one Gray code representation to another in order to escape local optima. Theoretical results that substantially improve our understanding of the Gray codes and the shifting mechanism are presented. New proofs also shed light on the number of unique Gray code neighborhoods accessible via shifting and on how neighborhood structure changes during shifting. We show that shifting can improve the performance of both a local search algorithm as well as one of the best genetic algorithms currently available.