@article{(Open Science Index):https://publications.waset.org/pdf/7053,
	  title     = {Evaluation of Evolution Strategy, Genetic Algorithm and their Hybrid on Evolving Simulated Car Racing Controllers},
	  author    = {Hidehiko Okada and  Jumpei Tokida},
	  country	= {},
	  institution	= {},
	  abstract     = {Researchers have been applying tional intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI
methods with respect to each game application. In th
our experimental result on the comparison of three evolutionary algorithms – evolution strategy, genetic algorithm, and their hybrid
applied to evolving controller agents for the CIG 2007 Simulated Car Racing competition. Our experimental result shows that, premature
convergence of solutions was observed in the case of ES, and GA outperformed ES in the last half of generations. Besides, a hybrid
which uses GA first and ES next evolved the best solution among the whole solutions being generated. This result shows the ability of GA in
globally searching promising areas in the early stage and the ability of ES in locally searching the focused area (fine-tuning solutions).},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {6},
	  number    = {5},
	  year      = {2012},
	  pages     = {707 - 710},
	  ee        = {https://publications.waset.org/pdf/7053},
	  url   	= {https://publications.waset.org/vol/65},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 65, 2012},
	}