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Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)最新文献

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Self-adaptive routing based on learning classifier systems 基于学习分类器系统的自适应路由
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330924
Chung-Yuan Huang, Chuen-Tsai Sun
{"title":"Self-adaptive routing based on learning classifier systems","authors":"Chung-Yuan Huang, Chuen-Tsai Sun","doi":"10.1109/CEC.2004.1330924","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330924","url":null,"abstract":"Successful computer and Internet networks require carefully designed routing protocols. The authors report on their attempt to apply evolutionary computations - that is, to place a learning classifier system on individual routers - to solve routing problems. We found that learning classifier systems are capable of fulfilling traditional routing protocol tasks (e.g., establishing routing tables) after a short period of training. Furthermore, they are capable of adapting to changing network environments and choosing the most efficient path available. Results from our experiments show that the system outperforms shortest path algorithms.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116425747","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
An investigation of an evolutionary approach to the opening of Go 对围棋开局演化方法的研究
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331149
G. Kendall, R. Yaakob, P. Hingston
{"title":"An investigation of an evolutionary approach to the opening of Go","authors":"G. Kendall, R. Yaakob, P. Hingston","doi":"10.1109/CEC.2004.1331149","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331149","url":null,"abstract":"The game of Go can be divided into three stages; the opening, the middle, and the end game. In this paper, evolutionary neural networks, evolved via an evolutionary strategy, are used to develop opening game playing strategies for the game. Go is typically played on one of three different board sizes, i.e., 9/spl times/9, 13/spl times/13 and 19/spl times/19. A 19/spl times/19 board is the standard size for tournament play but 9/spl times/9 and 13/spl times/13 boards are usually used by less-experienced players or for faster games. This work focuses on the opening, using a 13/spl times/13 board. A feed forward neural network player is played against a static player (Gondo), for the first 30 moves. Then Gondo takes the part of both players to play out the remainder of the game. Two experiments are presented which indicate that learning is taking place.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125729921","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: 12
A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems 数值基准问题差分进化、粒子群优化和进化算法的比较研究
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331139
J. Vesterstrom, R. Thomsen
{"title":"A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems","authors":"J. Vesterstrom, R. Thomsen","doi":"10.1109/CEC.2004.1331139","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331139","url":null,"abstract":"Several extensions to evolutionary algorithms (EAs) and particle swarm optimization (PSO) have been suggested during the last decades offering improved performance on selected benchmark problems. Recently, another search heuristic termed differential evolution (DE) has shown superior performance in several real-world applications. In this paper, we evaluate the performance of DE, PSO, and EAs regarding their general applicability as numerical optimization techniques. The comparison is performed on a suite of 34 widely used benchmark problems. The results from our study show that DE generally outperforms the other algorithms. However, on two noisy functions, both DE and PSO were outperformed by the EA.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126747255","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: 1303
An evolutionary algorithm method for sampling n-partite graphs n部图采样的一种进化算法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331177
Michel L. Goldstein, G. Yen
{"title":"An evolutionary algorithm method for sampling n-partite graphs","authors":"Michel L. Goldstein, G. Yen","doi":"10.1109/CEC.2004.1331177","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331177","url":null,"abstract":"The growth of use of graph-structured databases modeled on n-partite graphs has increased the ability to generate more flexible databases. However, the calculation of certain features in these databases may be highly resource-consuming. This work proposes a method for approximating these features by sampling. A discussion of the difficulty of sampling in n-partite graphs is made and an evolutionary algorithm-based method is presented that uses the information from a smaller subset of the graph to infer the amount of sampling needed for the rest of the graph. Experimental results are shown on a publications database on Anthrax for finding the most important authors.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121439031","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: 2
Cellz: a simple dynamic game for testing evolutionary algorithms Cellz:一个测试进化算法的简单动态游戏
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330972
S. Lucas
{"title":"Cellz: a simple dynamic game for testing evolutionary algorithms","authors":"S. Lucas","doi":"10.1109/CEC.2004.1330972","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330972","url":null,"abstract":"The game of Cellz has been designed as a test bed for evolutionary algorithms. The game has a minimal set of rules that nonetheless offer the possibility for complex behaviour to emerge. Computationally, the game is cheap to simulate, which leads to rapid runs of evolutionary algorithms. A key feature of the game is the cell division process, which can lead to evolution in situ without reference to any externally defined fitness function. This paper describes the rationale behind the development of Cellz, the rules of the game and the software interfaces for the cell controllers. The randomness in the game initialisation leads to extremely noisy fitness functions, which adds to the challenge of evolving high-performance controllers. Initial results demonstrate that an evolved perceptron-type controller can achieve mediocre performance on the single species game.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"8 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127773280","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: 19
Asymmetric cell division in artificial evolution 人工进化中的不对称细胞分裂
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331167
P. E. Hotz
{"title":"Asymmetric cell division in artificial evolution","authors":"P. E. Hotz","doi":"10.1109/CEC.2004.1331167","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331167","url":null,"abstract":"Increasingly often artificial evolutionary techniques are coupled with mechanisms abstracted from developmental biology. For instance, artificial cells endowed with genetic regulatory networks were used to evolve and develop simulated creatures. With the evolution of a simple vermicular structure it is shown that asymmetric cell division is useful for the positioning of cells and that this mechanism can be integrated with other developmental mechanisms such as genetic regulation and cell adhesion to get moving artificial creatures. Surprisingly, the movements were controlled by the genetic regulatory network alone without the need to evolve a neural structure.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127387911","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: 3
Genetic list scheduling for soft real-time parallel applications 软实时并行应用的遗传列表调度
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330993
Yoginder S. Dandass
{"title":"Genetic list scheduling for soft real-time parallel applications","authors":"Yoginder S. Dandass","doi":"10.1109/CEC.2004.1330993","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330993","url":null,"abstract":"This paper presents a hybrid algorithm that combines list scheduling with a genetic algorithm for constructing nonpreemptive schedules for soft real-time parallel applications represented as directed acyclic graphs. The execution time requirements of the applications' tasks are assumed to be stochastic and are represented as probability distribution functions. The approach presented here produces shorter schedules than two popular list scheduling approaches for a majority of sample problems. Furthermore, the stochastic schedules provide a mechanism for predicting the probability of the application completing when the execution time available is less than the worst case requirement.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"54 46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122241330","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: 4
An effective evolutionary strategy for bijective S-boxes 双目标s盒的有效进化策略
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331158
Hua Chen, D. Feng
{"title":"An effective evolutionary strategy for bijective S-boxes","authors":"Hua Chen, D. Feng","doi":"10.1109/CEC.2004.1331158","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331158","url":null,"abstract":"Being as unique nonlinear components of block ciphers, S-boxes control the security of the cryptographic algorithms. The design of S-boxes with genetic algorithms is a recent research focus. For the popular bijective S-boxes, an effective evolutionary strategy is given in this paper, including fitness function, breeding strategy and hill climbing algorithm. Under this strategy, an effective genetic algorithm for 8 /spl times/ 8 bijective S-boxes is provided and a large number of S-boxes with high nonlinearity and low difference uniformity can be obtained.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134302113","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: 13
A memetic co-clustering algorithm for gene expression profiles and biological annotation 基因表达谱和生物注释的模因共聚类算法
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1331091
N. Speer, C. Spieth, A. Zell
{"title":"A memetic co-clustering algorithm for gene expression profiles and biological annotation","authors":"N. Speer, C. Spieth, A. Zell","doi":"10.1109/CEC.2004.1331091","DOIUrl":"https://doi.org/10.1109/CEC.2004.1331091","url":null,"abstract":"With the invention of microarrays, researchers are capable of measuring thousands of gene expression levels in parallel at various time points of the biological process. To investigate general regulatory mechanisms, biologists cluster genes based on their expression patterns. In this paper, we propose a new memetic co-clustering algorithm for expression profiles, which incorporates a priori knowledge in the form of gene ontology information. Ontologies offer a mechanism to capture knowledge in a shareable form that is also processable by computers. The use of this additional annotation information promises to improve biological data analysis and simplifies the identification of processes that are relevant under the measured conditions.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134510271","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: 41
A new technique for dynamic size populations in genetic programming 遗传规划中动态大小群体的一种新技术
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI: 10.1109/CEC.2004.1330896
M. Tomassini, L. Vanneschi, Jerome Cuendet, F. Fernández
{"title":"A new technique for dynamic size populations in genetic programming","authors":"M. Tomassini, L. Vanneschi, Jerome Cuendet, F. Fernández","doi":"10.1109/CEC.2004.1330896","DOIUrl":"https://doi.org/10.1109/CEC.2004.1330896","url":null,"abstract":"New techniques for dynamically changing the size of populations during the execution of genetic programming systems are proposed. Two models are presented, allowing to add and suppress individuals on the basis of some particular events occurring during the evolution. These models allow to find solutions of better quality, to save considerable amounts of computational effort and to find optimal solutions more quickly, at least for the set of problems studied here, namely the artificial ant on the Santa Fe trail, the even parity 5 problem and one instance of the symbolic regression problem. Furthermore, these models have a positive effect on the well known problem of bloat and act without introducing additional computational cost.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122442272","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: 42
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