Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Efficient reinforcement learning through symbiotic evolution
Machine Learning - Special issue on reinforcement learning
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Advances in Engineering Software
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Test Examples for Nonlinear Programming Codes
Test Examples for Nonlinear Programming Codes
Inference of a gene regulatory network by means of interactive evolutionary computing
Information Sciences—Informatics and Computer Science: An International Journal - Bioinformatics-selected papers from 4th CBGI & 6th JCIS Proceedings
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Using Genetic Algorithms with Small Populations
Proceedings of the 5th International Conference on Genetic Algorithms
A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling
Computers and Operations Research
Advances in Engineering Software
Journal of Global Optimization
A Fuzzy Adaptive Differential Evolution Algorithm
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Expert Systems with Applications: An International Journal
A hierarchical genetic algorithm for segmentation of multi-spectral human-brain MRI
Expert Systems with Applications: An International Journal
Genetic algorithms as global random search methods: An alternative perspective
Evolutionary Computation
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Expert Systems with Applications: An International Journal
On genetic algorithms for shoe making nesting - A Taiwan case
Expert Systems with Applications: An International Journal
Study of genetic algorithm with reinforcement learning to solve the TSP
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A hybrid genetic algorithm for no-wait job shop scheduling problems
Expert Systems with Applications: An International Journal
Genetic algorithm approach for solving a cell formation problem in cellular manufacturing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Research of multi-population agent genetic algorithm for feature selection
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hierarchical genetic algorithms operating on populations of computer programs
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
GA-TSKfnn: Parameters tuning of fuzzy neural network using genetic algorithms
Expert Systems with Applications: An International Journal
Two-phase sub population genetic algorithm for parallel machine-scheduling problem
Expert Systems with Applications: An International Journal
Statistics-based adaptive non-uniform mutation for genetic algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
IEEE Transactions on Information Technology in Biomedicine
Genetic reinforcement learning through symbiotic evolution forfuzzy controller design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems
IEEE Transactions on Fuzzy Systems
A genetic approach to standard cell placement using meta-genetic parameter optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Distributed genetic algorithms for the floorplan design problem
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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The main theme of this paper is to present a novel evolution, the genetic regulatory network-based symbiotic evolution (GRNSE), to improve the convergent speed and solution accuracy of genetic algorithms. The proposed GRNSE utilizes genetic regulatory network (GRN) reinforcement learning to improve the diversity and symbiotic evolution (SE) initialization to achieve the parallelism. In particular, GRN-based learning increases the global rate by regulating members of genes in symbiotic evolution. To compare the efficiency of the proposed method, we adopt 41 benchmarks that contain many nonlinear and complex optimal problems. The influences of dimension, individual population size, and gene population size are examined. A new control parameter, the population rate is introduced to initiate the ratio between the gene and chromosome. Finally, all the studies of there 41 benchmarks demonstrate that from the statistic point of view, GRNSE give a better convergence speed and a more accurate optimal solution than GA and SE.