Foundations of Genetic Algorithms 2003 (FOGA 7) (Hardcover)

Kenneth A. Dejong, Ricardo Poli, Jonathan E. Rowe, Ke

  • 出版商: Morgan Kaufmann
  • 出版日期: 2003-06-03
  • 定價: $2,800
  • 售價: 8.0$2,240
  • 語言: 英文
  • 頁數: 416
  • 裝訂: Hardcover
  • ISBN: 0122081552
  • ISBN-13: 9780122081552
  • 相關分類: Algorithms-data-structures
  • 立即出貨(限量) (庫存=5)



Foundations of Genetic Algorithms, Volume 7 (FOGA-7) is a collection of 22 papers written by the field's leading researchers, representing the most current, state-of-the-art research both in GAs and in evolutionary computation theory in general. Much more than proceedings, this clothbound book and its companion six volumes document the bi-annual FOGA workshops since their inception in 1990. Before publication, each paper is peer reviewed, revised, and edited. Covering the variety of analysis tools and techniques that characterize the behavior of evolutionary algorithms, the FOGA series, with its brand-new volume 7, provides the single best source of reference for the theoretical work in this field.


Editorial Introduction; Schema Analysis of OneMax Problem: Evolution Equation for First Order Schemata; Partitioning, Epistasis, and Uncertainty; A Schema-theory-based Extension of Geiringer's Theorem for Linear GP and Variable-length GAs under Homologous Crossover; Bistability in a Gene Pool GA with Mutation; The 'Crossover Landscape' and the [exclamdown][yen]Hamming Landscape[exclamdown][[brvbar]] for Binary Search Spaces; Modelling Finite Populations; The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove It; Evolutionary Algorithms and the Boltzmann Distribution; Modeling and Simulating Diploid Simple Genetic Algorithms; On the Evolution of Phenotypic Exploration Distributions; How many Good Programs are there? How Long are they?; Modeling Variation in Cooperative Coevolution Using Evolutionary Game Theory; A Mathematical Framework for the Study of Coevolution; Guaranteeing Coevolutionary Objective Measures; A New Framework for the Valuation of Algorithms for Black-Box Optimization; A Study on the Performance of the (1+1)-Evolutionary Algorithm; The Long Term Behavior of Genetic Algorithms with Stochastic Evaluation; On the Behavior of [florin]v[florin][Yacute][florin]1[florin]z[florin]n[florin]Ü[florin]w[florin]ES Optimizing Functions Disturbed by Generalized Noise; Parameter Perturbation Mechanisms in Binary Coded GAs with Self-Adaptive Mutation; Fitness Gains and Mutation Patterns: Deriving Mutation Rates by Exploiting Landscape Data; Towards Qualitative Models of Interactions in Evolutionary Algorithms; Genetic Search Reinforced by the Population Hierarchy



- 編者引言
- OneMax問題的Schema分析:一階Schema的演化方程
- 分割、表徵關聯性和不確定性
- 基於Schema理論的線性遺傳規劃和可變長度遺傳演算法在同源交叉下的Geiringer定理擴展
- 具突變的基因池遺傳演算法中的雙穩態
- 二進制搜索空間的“交叉風景”和“漢明風景”
- 有限族群建模
- PBIL對學習率的敏感性以及如何通過詳細平衡來消除敏感性
- 遺傳演算法和玻爾茨曼分佈
- 建模和模擬二倍體簡單遺傳演算法
- 關於表型探索分佈的演化
- 有多少好的程式?它們有多長?
- 使用演化博弈理論建模合作共進化的變異
- 用於共進化研究的數學框架
- 保證共進化目標度量
- 用於黑盒優化算法評估的新框架
- 關於(1+1)-演化算法性能的研究
- 具有隨機評估的遺傳演算法的長期行為
- 關於受到廣義噪聲干擾的[v][Y][z][n][U][w][ES]優化函數行為的研究
- 自適應突變的二進制編碼遺傳演算法中的參數擾動機制
- 基於景觀數據推導突變率的適應度增益和突變模式
- 進化演算法中交互作用的定性模型
- 由族群等級強化的遺傳搜索