2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI)最新文献_第2页

Relational algebra for multi-ranked similarity-based databases 基于多级相似度数据库的关系代数

2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Pub Date : 2013-04-16 DOI: 10.1109/FOCI.2013.6602448

R. Belohlávek, Vilém Vychodil

引用次数: 3

Influence of selective pressure on quality of solutions and speed of evolutionary mastermind 选择压力对解决方案质量和进化思维速度的影响

2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Pub Date : 2013-04-16 DOI: 10.1109/FOCI.2013.6602464

J. J. M. Guervós, A. García, C. Cotta, Nuria Rico

{"title":"Influence of selective pressure on quality of solutions and speed of evolutionary mastermind","authors":"J. J. M. Guervós, A. García, C. Cotta, Nuria Rico","doi":"10.1109/FOCI.2013.6602464","DOIUrl":"https://doi.org/10.1109/FOCI.2013.6602464","url":null,"abstract":"Mastermind is a puzzle in which a hidden code of length ℓ and made with κ colors has to be discovered via making guesses of the code and receiving hints that express the distance from the guess to the code, in terms of number of symbols in the right position and with the right color. Solutions to these problem are mainly heuristic and thus finding the correct parameters for these solutions has to be done via systematic experimentation. Since diversity in the population is one of the main factors affecting performance, in this paper we will experiment with selective pressure via two different parameters: population size and size of tournament in tournament selection. We will study the influence of them in three different measures: algorithm performance (measured in average number of guesses needed), number of evaluations and time needed to find the solution. We will prove that while, in general, increasing population size improves performance, there is an optimal size over which no further improvement is achieved. On the other hand, tournament size does not have a clear influence on performance, although it influences time needed to find the solution. We will also show that the number of evaluations is correlated positively with time, and it increases with population size so that a trade-off has to be found among solution quality and population size. After evaluating the result of the experiments, we will try to advance a rule of thumb for sizing population for the general MasterMind problem.","PeriodicalId":237129,"journal":{"name":"2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132268822","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

The impact of varying resources available to Iterated Prisoner's Dilemma agents 不同资源对迭代囚徒困境代理人的影响

2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Pub Date : 2013-04-16 DOI: 10.1109/FOCI.2013.6602456

D. Ashlock, Eun-Youn Kim

引用次数: 15

A review of computational intelligence in RTS games 回顾RTS游戏中的计算智能

2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Pub Date : 2013-04-16 DOI: 10.1109/FOCI.2013.6602463

R. Lara-Cabrera, C. Cotta, Antonio J. Fernández

引用次数: 53

Radial basis functions for multidimensional learning with an application to nondestructive sizing of defects 多维学习的径向基函数及其在缺陷无损测量中的应用

2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Pub Date : 2013-04-16 DOI: 10.1109/FOCI.2013.6602453

S. S. Ahmed, B. Rao, T. Jayakumar

{"title":"Radial basis functions for multidimensional learning with an application to nondestructive sizing of defects","authors":"S. S. Ahmed, B. Rao, T. Jayakumar","doi":"10.1109/FOCI.2013.6602453","DOIUrl":"https://doi.org/10.1109/FOCI.2013.6602453","url":null,"abstract":"A computational intelligence problem with mapping of multiple classes for a given input feature is addressed in this paper. The objective is to classify a vector of class for a given vector of input features. Each class is a member of disjoint set called dimension and hence, it is called multidimensional learning. Dependency between the classes and dimensions are usually not taken into account while constructing independent classifiers for each component class of vector. In this paper, two methods of adaption of radial basis functions (RBF) neural network for multidimensional learning are proposed. In first method, the prototype vector of hidden layer is formed by cluster analysis on instance belong to each class of each dimension. By this way the dependencies of classes is considered. In second method, the prototype vector of hidden layer are formed by cluster analysis on instance belong to each new classes by taking the Cartesian product of each dimension. With this method, the dependency between each dimension is concentrated. A comparison study with these two methods of adaptations with independent uni-dimensional RBF is presented. Studies are carried out with real world multidimensional dataset (with >2 classes in each dimension) obtained from simulated eddy current non-destructive evaluation (NDE) of a stainless steel plate having sub-surface defects of different dimensions. This dataset is used for estimating three characteristics (three dimensions) of defects namely, length, depth and height. The performance evaluation using metrics such as mean accuracy and global accuracy clearly reveals that the proposed multidimensional RBF is superior to the uni-dimensional RBF used individually for each dimensions.","PeriodicalId":237129,"journal":{"name":"2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133549116","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

Evaluation scheduling in noisy environments 噪声环境下的评估调度

2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Pub Date : 2013-04-16 DOI: 10.1109/FOCI.2013.6602457

James R. Glenn

引用次数: 1

Analysis of SpikeProp convergence with alternative spike response functions 具有备选尖峰响应函数的SpikeProp收敛性分析

2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI) Pub Date : 2013-04-16 DOI: 10.1109/FOCI.2013.6602461

Vaenthan Thiruvarudchelvan, J. Crane, T. Bossomaier

引用次数: 8