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Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)最新文献

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Evolving sufficient robot controllers 进化出足够的机器人控制器
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592361
Henrik Hautop Lund, J. Hallam
{"title":"Evolving sufficient robot controllers","authors":"Henrik Hautop Lund, J. Hallam","doi":"10.1109/ICEC.1997.592361","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592361","url":null,"abstract":"Different methods exist for reducing the time consumption in evolutionary robotics experiments. One is to use simulations, while another is to evolve controllers that are no more complex than task fulfilment requires. Behaviors such as exploration and homing, that seemingly demand a complex control system, only require a perceptron that connects a robot's sensors to its motors. This is shown by evolving such neurocontrollers for the Khepera robot. An exploitation of the robot's perception of the environment's geometrical shape allows the robot to encode time, even though explicitly it is not presented with the time and there are no recurrent connections in the neurocontroller.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131595070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 38
Solving 3-SAT by GAs adapting constraint weights 用自适应约束权的GAs求解3-SAT
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592273
A. Eiben, J.K. van der Hauw
{"title":"Solving 3-SAT by GAs adapting constraint weights","authors":"A. Eiben, J.K. van der Hauw","doi":"10.1109/ICEC.1997.592273","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592273","url":null,"abstract":"Handling NP complete problems with GAs is a great challenge. In particular the presence of constraints makes finding solutions hard for a GA. In this paper we present a problem independent constraint handling mechanism, Stepwise Adaptation of Weights (SAW), and apply it for solving the 3-SAT problem. Our experiments prove that the SAW mechanism substantially increases GA performance. Furthermore, we compare our SAW-ing GA with the best heuristic technique we could trace, WGSAT, and conclude that the GA is superior to the heuristic method.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124256131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 63
Reducing computational expense associated with evolutionary detailed design 减少与进化细节设计相关的计算费用
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592341
H. Vekeria, I. Parmee
{"title":"Reducing computational expense associated with evolutionary detailed design","authors":"H. Vekeria, I. Parmee","doi":"10.1109/ICEC.1997.592341","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592341","url":null,"abstract":"This paper provides a comparison of Adaptive Search methods for the reduction in computational expense associated with the optimisation of highly dimensional structural design problems. A sequential method for Dynamic Shape Refinement is presented. This technique utilises problem representations of varying complexity, from a coarse representation which is gradually refined until the desired level is achieved. This paper also presents the Injection Island Genetic Algorithm (iiGA). The technique utilises a number of levels of varying resolution grids, each evolving as a separate process. The iiGA method is further extended by the utilisation of a dynamic method of plate representation which performs on-line replacement of the lower resolution subpopulations with finer representations. The results show a significant improvement over those obtained utilising single level representations in terms of a reduction in computational expense, whilst also achieving significant improvements in design performance.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116119410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Enhancing recombination with the Complementary Surrogate Genetic Algorithm 利用互补替代遗传算法增强重组
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592276
I. K. Evans
{"title":"Enhancing recombination with the Complementary Surrogate Genetic Algorithm","authors":"I. K. Evans","doi":"10.1109/ICEC.1997.592276","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592276","url":null,"abstract":"In traditional genetic algorithm (GA) approaches using finite populations, recombination alone has been shown to be insufficient to guarantee optimal solutions because of the well known problems of fixation of alleles and premature convergence. Mutation is widely regarded as critical to preserve diversity in recombination dominant GAs, as well as a powerful search heuristic in its own right; mutation is central to recent GA convergence proofs. The paper examines an alternate genetic algorithm with no explicit mutation operator. The Complementary Surrogate GA (CSGA) uses traditional crossover operators, but guarantees recombination access to the complete search space by modifying the GA population structure. Complementary Surrogate Sets (CSS) within the population ensure allele diversity at each locus, while allowing standard selection methods to work as expected. A proof of convergence is provided as well as the results of an empirical study examining the CSGA using various CSS strategies on standard function optimization benchmarks.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"616 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122943557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Genetic local search for the TSP: new results TSP基因局部搜索:新结果
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592288
P. Merz, Bernd Freisleben
{"title":"Genetic local search for the TSP: new results","authors":"P. Merz, Bernd Freisleben","doi":"10.1109/ICEC.1997.592288","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592288","url":null,"abstract":"The combination of local search heuristics and genetic algorithms has been shown to be an effective approach for finding near-optimum solutions to the traveling salesman problem. Previously proposed genetic local search algorithms for the symmetric and asymmetric traveling salesman problem are revisited and potential improvements are identified. Since local search is the central component in which most of the computation time is spent, improving the efficiency of the local search operators is crucial for improving the overall performance of the algorithms. The modifications of the algorithms are described and the new results obtained are presented. The results indicate that the improved algorithms are able to arrive at better solutions in significantly less time.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125185887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 279
An evolutionary approach to color image quantization 彩色图像量化的一种进化方法
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592355
Bernd Freisleben, A. Schrader
{"title":"An evolutionary approach to color image quantization","authors":"Bernd Freisleben, A. Schrader","doi":"10.1109/ICEC.1997.592355","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592355","url":null,"abstract":"In order to visualize true color images on graphic displays with reduced color resolution, a color quantization process is required. Since color quantization is an NP-hard optimization problem, several suboptimal heuristic approaches, with quite different objectives and results, have been proposed. We present a new hybrid approach in which an evolutionary algorithm is combined with a well-known local search heuristic. The superiority of the proposed approach to other strategies used in color quantization is demonstrated by presenting results for some test images.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127353305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
Model-based evolutionary computing: a neural network and genetic algorithm architecture 基于模型的进化计算:一种神经网络和遗传算法架构
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592384
L. Bull
{"title":"Model-based evolutionary computing: a neural network and genetic algorithm architecture","authors":"L. Bull","doi":"10.1109/ICEC.1997.592384","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592384","url":null,"abstract":"Traditional evolutionary computing uses an explicit fitness function-mathematical or simulated-to derive a solution to a problem from a population of individuals, over a number of generations. In this paper an architecture is presented which allows such techniques to be used on problems which cannot be expressed mathematically or which are difficult to simulate. A neural network is trained using example individuals with their explicit fitness and the resulting model of the fitness function is then used by the evolutionary algorithm to find a solution. It is shown that the approach is effective over a wide range of function types in comparison to the traditional approach. Finally its application to a user-agent task is described-a system in which the fitness function is purely subjective.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127461389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
A genetic algorithm for task distribution 任务分配的遗传算法
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592381
T. Drabe, W. Bressgott
{"title":"A genetic algorithm for task distribution","authors":"T. Drabe, W. Bressgott","doi":"10.1109/ICEC.1997.592381","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592381","url":null,"abstract":"A genetic algorithm is presented to assemble tasks to clusters which are performed by neural network modules. Simulations on letter recognition are compared to those obtained by a monolithic network and by a modular architecture with randomly composed clusters. The proposed method proves superior in terms of final convergence speed, generalization and completeness of solutions.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125753327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
New parallel hybrid genetic algorithm based on molecular dynamics approach for energy minimization of atomistic systems 基于分子动力学方法的原子系统能量最小化新并行混合遗传算法
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592280
M. Celino, P. Palazzari, N. Pucello, M. Rosati, V. Rosato
{"title":"New parallel hybrid genetic algorithm based on molecular dynamics approach for energy minimization of atomistic systems","authors":"M. Celino, P. Palazzari, N. Pucello, M. Rosati, V. Rosato","doi":"10.1109/ICEC.1997.592280","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592280","url":null,"abstract":"A hybrid genetic algorithm (HGA) for the optimization of the ground state structure of a metallic atomic cluster has been implemented on a MIMD-SIMD parallel platform. The concept of building block (BB) is generalized to cover this real coded optimization problem. On the basis of some reasonings on the dependence of the convergence of genetic algorithms (GAs) from BBs, a hybrid genetic algorithm (HGA) is proposed to solve the minimization problem. All the elements of each new population are optimized through a molecular dynamics algorithm: the aim of MD is to create ever better BBs and, consequently, to improve the convergence of GAs. HGA has been implemented on a MIMD-SIMD platform based on the massively parallel processing supercomputer Quadrics/APE100, which offers a peak performance of 25.6 Gflops; we obtained a sustained computational power greater than 10 Gflops.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"15 4 Pt 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116854037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Robust encodings in genetic algorithms: a survey of encoding issues 遗传算法中的鲁棒编码:编码问题综述
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) Pub Date : 1997-04-13 DOI: 10.1109/ICEC.1997.592265
S. Ronald
{"title":"Robust encodings in genetic algorithms: a survey of encoding issues","authors":"S. Ronald","doi":"10.1109/ICEC.1997.592265","DOIUrl":"https://doi.org/10.1109/ICEC.1997.592265","url":null,"abstract":"Problems of encoding brittleness have been observed in the genetic algorithm (GA) literature, where slightly different problems require completely different genetic encodings for good solutions to be found. As research continues into GA encoding schemes the idea of encoding robustness becomes more important. A robust encoding is one which will be effective for a wide range of problem instances that it was designed for. A robust encoding will also be amenable to modification or extension to solve different problem types. This paper is a survey of some of the practical and theoretical considerations vital to the construction of a more robust encoding which will allow the GA to solve a broader range of problem types.","PeriodicalId":167852,"journal":{"name":"Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121568636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 65
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