2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)最新文献_第2页

Examination of multi-objective optimization method for global search using DIRECT and GA 基于DIRECT和遗传算法的全局搜索多目标优化方法研究

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4631125

Luyi Wang, Hiroyuki Ishida, T. Hiroyasu, M. Miki

引用次数: 17

Investigation of simply coded evolutionary artificial neural networks on robot control problems 简单编码进化人工神经网络在机器人控制问题上的研究

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4631088

Y. Katada, Jun Nakazawa

引用次数: 1

Exploring the use of ancestry as a unified network model of finite population evolution 探索使用祖先作为有限种群进化的统一网络模型

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4631303

P. Whigham, Grant Dick

{"title":"Exploring the use of ancestry as a unified network model of finite population evolution","authors":"P. Whigham, Grant Dick","doi":"10.1109/CEC.2008.4631303","DOIUrl":"https://doi.org/10.1109/CEC.2008.4631303","url":null,"abstract":"The evolution of a population is determined by many factors, including the geographic separation of individuals in the population (spatial structure), parent selection via assortative mating (biasing who breeds with whom), environmental gradients, founder effects, disturbance, selection, stochastic effects characterised as genetic drift and so on. Ultimately the interest in studying a population of organisms is about characterising parent selection over time. This paper will examine the evolution of a population under the neutral conditions of genetic drift and for a simple selection model. For drift two conditions are considered: the first is for a range of spatial (geographic) constraints defined by a network; the second is through the use of a tagging system that models assortative mate selection. A simple selection model for the OneMax problem is used to illustrate the response of a population to selection pressure. An ancestry network is constructed representing the shared parent interactions over time. This structure is analyzed as a method for characterising the interactions of a population. The approach demonstrates a unified model to characterise population dynamics, independent of the underlying evolutionary constraints.","PeriodicalId":328803,"journal":{"name":"2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127144248","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

Towards a self regulating local network neighbourhood artificial immune system for data clustering 面向数据聚类的自调节局部网络邻域人工免疫系统

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4630862

A. J. Graaff, A. Engelbrecht

引用次数: 1

Solving and analyzing Sudokus with cultural algorithms 用文化算法解决和分析数独

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4631350

Timo Mantere, J. Koljonen

引用次数: 31

A Coalition-Based Metaheuristic for the vehicle routing problem 基于联盟的车辆路径问题元启发式算法

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4630945

D. Meignan, Jean-Charles Créput, A. Koukam

引用次数: 30

Model-building algorithms for multiobjective EDAs: Directions for improvement 多目标eda的模型构建算法:改进方向

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4631179

Luis Martí, Jesús García, A. Berlanga, J. M. Molina

引用次数: 14

An evolutionary algorithm for discovering biclusters in gene expression data of breast cancer 发现乳腺癌基因表达数据双聚类的进化算法

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4630892

Qinghua Huang, Minhua Lu, Hong Yan

引用次数: 5

Robust model matching control of immune systems under environmental disturbances: Fuzzy dynamic game approach 环境干扰下免疫系统鲁棒模型匹配控制:模糊动态博弈方法

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4631075

Chia-Hung Chang, Bor‐Sen Chen, Y. Chuang

{"title":"Robust model matching control of immune systems under environmental disturbances: Fuzzy dynamic game approach","authors":"Chia-Hung Chang, Bor‐Sen Chen, Y. Chuang","doi":"10.1109/CEC.2008.4631075","DOIUrl":"https://doi.org/10.1109/CEC.2008.4631075","url":null,"abstract":"A robust model matching control of immune response is proposed for therapeutic enhancement to match a prescribed immune response under uncertain initial states and environmental disturbances, including continuous intrusion of exogenous pathogens. The worst-case effect of all possible environmental disturbances and uncertain initial states on the matching for a desired immune response is minimized for the enhanced immune system, i.e. a robust control is designed to track a prescribed immune model response from the minimax matching perspective. This minimax matching problem could be transformed to an equivalent dynamic game problem. The exogenous pathogen and environmental disturbances are considered as a player to maximize (worsen) the matching error when the therapeutic control agents are considered as another player to minimize the matching error. Since the innate immune system is highly nonlinear, it is not easy to solve the robust model matching control problem by the nonlinear dynamic game method directly. A fuzzy model is proposed to interpolate several linearized immune systems at different operation points to approximate the innate immune system via smooth fuzzy membership functions. With the help of fuzzy approximation method, the minimax matching control problem of immune systems could be easily solved by the proposed fuzzy dynamic game method via the linear matrix inequality (LMI) technique with the help of robust control toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed method.","PeriodicalId":328803,"journal":{"name":"2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114908109","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

Epigenetic sensorimotor pathways and its application to developmental object learning 表观遗传感觉运动通路及其在发展性客体学习中的应用

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Pub Date : 2008-06-01 DOI: 10.1109/CEC.2008.4631333

Zhengping Ji, M. Luciw, J. Weng

{"title":"Epigenetic sensorimotor pathways and its application to developmental object learning","authors":"Zhengping Ji, M. Luciw, J. Weng","doi":"10.1109/CEC.2008.4631333","DOIUrl":"https://doi.org/10.1109/CEC.2008.4631333","url":null,"abstract":"A pathway in the central nervous system (CNS) is a path through which nervous signals are processed in an orderly fashion. A sensorimotor pathway starts from a sensory input and ends at a motor output, although almost all pathways are not simply unidirectional. In this paper, we introduce a simple, biologically inspired, unified computational model - Multi-layer In-place Learning Network (MILN), with a design goal to develop a recurrent network, as a function of sensorimotor signals, for open-ended learning of multiple sensorimotor tasks. The biologically motivated MILN provides automatic feature derivation and pathway refinement from the temporally real-time inputs. The work presented here is applied in the challenging application field of developing reactive behaviors from a video camera and a (noisy) radar range sensor for a vehicle-based robot in open, natural driving environments. An internal model of the agentpsilas experience of the environments is created and refined from the ground-up using a cell-centered model, based on the genomic equivalence principle. The outputs can be imposed by a teacher, at the same time as the learning is active. At any time instant, sensory information from the radar allows the system to focus its visual analysis on relatively small areas within the image plane (attention selection), in a computationally efficient way, suitable for real-time training. This system was trained with data from 10 different city and highway road environments, and cross validation shows that MILN was able to correctly recognize above 95% of the radar-extracted images from the multiple environments. The in-place learning mechanism compares with other learning algorithms favorably, as results of a comparison indicate that in-place learning is the only one to fit all the specified criteria of development of a general-purpose sensorimotor pathway.","PeriodicalId":328803,"journal":{"name":"2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114949539","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