A Multi-Agent Architecture for Business Process Management Adapts to Unreliable Performance

Table of Contents

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   Book Overview
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   Chapter 1 Pareto Solutions of Multipoint Design of Supersonic Wings Using Evolutionary Algorithms
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   Chapter 2 Notes on Design Through Artificial Evolution: Opportunities and Algorithms
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   Chapter 3 Testing, Evaluation and Performance of Optimization and Learning Systems
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   Chapter 4 From Evolutionary Computation to Natural Computation
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   Chapter 5 Experience with Hybrid Evolutionary/local Optimization for Process Design
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   Chapter 6 The Development of a Grid-based Engineering Design Problem Solving Environment.
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   Chapter 7 A Hybrid Search Technique for Inverse Transient Analysis in Water Distribution Systems
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   Chapter 8 Optimisation of Thermal Power Plant Designs: A Graph-based Adaptive Search Approach
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    Chapter 9 Genetic Algorithm Search for Stent Design Improvements
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    Chapter 10 A Multiobjective Optimisation Approach for the Conceptual Design of Frame Structures
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    Chapter 11 Multi-Objective Evolutionary Topological Optimum Design
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    Chapter 12 Better Surface Intersections by Constrained Evolution
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    Chapter 13 Inverse Identification of Boundary Constants for Electronic Packages Using Modified Micro Genetic Algorithm and Reduced-basis Method
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    Chapter 14 Extrinsic Evolution of Finite State Machine
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    Chapter 15 Neural Computing Approach to Shape Change Estimation in Hot Isostatic Pressing
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    Chapter 16 Multi-criterion Tackling Bottleneck Machines and Exceptional Parts in Cell Formation Using Genetic Algorithms
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    Chapter 17 Adaptive Computing in Design and Manufacture V
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    Chapter 18 Evolutionary Multicriteria Optimization for Improved Design of Optimal Control Systems
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    Chapter 19 Explorations in Fuzzy Classifier System Architectures
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    Chapter 20 Evolving Temporal Rules with the Delayed Action Classifier System — Analysis and New Results
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    Chapter 21 Adaptive Image Segmentation Based on Visual Interactive Feedback Learning
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    Chapter 22 Adapting Problem Specifications and Design Solutions Using Co-evolution
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    Chapter 23 Handling Constraints in Genetic Algorithms Using Dominance-based Tournaments
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    Chapter 24 The Optimisation of Multivariate Robust Design Criteria
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    Chapter 25 Learning from Experience: Case Injected Genetic Algorithm Design of Combinational Logic Circuits
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    Chapter 26 Constrained Optimisation with the Fuzzy Clustering Evolution Strategy
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    Chapter 27 Constrained Optimization Using an Evolutionary Programming-based Cultural Algorithm
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    Chapter 28 A Data Mining Tool Using An Intelligent Processing System with a Clustering Application
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    Chapter 29 Full Elite Sets for Multi-objective Optimisation
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    Chapter 30 Agent-based Support within an Interactive Evolutionary Design System
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    Chapter 31 A Multi-Agent Architecture for Business Process Management Adapts to Unreliable Performance
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    Chapter 32 Real-time Co-ordinated Scheduling Using a Genetic Algorithm