Agent-based computing /

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Bouça, Duarte, Gafagnão, Amaro
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Nova Science Publishers, [2010].
Colección:Computer science, technology and applications.
Temas:
Intelligent agents (Computer software)
Distributed artificial intelligence.
Data mining.
Agents intelligents (Logiciels)
Intelligence artificielle répartie.
Exploration de données (Informatique)
COMPUTERS > Enterprise Applications > Business Intelligence Tools.
COMPUTERS > Intelligence (AI) & Semantics.
Data mining
Distributed artificial intelligence
Acceso en línea:Texto completo
Tabla de Contenidos:
  • AGENT-BASED COMPUTING
  • AGENT-BASED COMPUTING
  • CONTENTS
  • PREFACE
  • AGENT-BASED GENETIC ALGORITHM FOR GLOBAL NUMERICAL OPTIMIZATION AND FEATURE SELECTION
  • 1. INTRODUCTION
  • 2. CHAIN-LIKE AGENT GENETIC ALGORITHM FOR GLOBAL NUMERICAL OPTIMIZATION AND FEATURE SELECTION
  • 2.1. Analysis of Algorithm
  • 2.1.1. Chain-Like Agent Structure
  • 2.1.2. Selection Process Based on Dynamic Neighboring Competition Strategy
  • 2.1.3. Neighboring Crossover Process
  • 2.1.4. Adaptive Mutation Process
  • 2.1.5. Stop Criterion
  • 2.1.6. Elitism Strategy
  • 2.1.7. Realization of Algorithm 2.2. Experimental Results
  • 2.2.1. Global Numerical Optimization Experiments
  • 2.2.2. Feature Selection Experiments
  • 2.3. Conclusions
  • 3. MULTIPLE-POPULATION CHAIN-LIKE AGENT GENETIC ALGORITHM FOR GLOBAL NUMERICAL OPTIMIZATION AND FEATURE SELECTION
  • 3.1. Analysis of Algorithm
  • 3.1.1. Multi-Population Cycle Chain-Like Agent Structure
  • 3.1.2. Genetic Operators
  • 3.1.3. Realization of Algorithm
  • 3.1.4. Computational Complexity
  • 3.2. Experimental Results
  • 3.2.1. Global Numerical Optimization Experiments
  • 3.2.2. Feature Selection Experiments3.3. Conclusions
  • CONCLUSIONS AND FUTURE WORK
  • ACKNOWLEDGMENTS
  • REFERENCES
  • MULTI-AGENT ENTERPRISE SUSTAINABILITY PERFORMANCE MEASUREMENT SYSTEM
  • ABSTRACT
  • INTRODUCTION
  • METHODOLOGY
  • SUSTAINABILITY AGENT
  • 1. The Selection of Suitable Indicators
  • 2. Retrieving data from Data Repository Agent
  • 3. Calculating the Weights of Indicators
  • 4. Calculating Sustainability Performance Indices by Using MCDM Methods
  • DATA REPOSITORY AGENT
  • ALERT MANAGEMENT AGENT
  • COMMUNICATION AGENT
  • APPLICATION Sustainability Agent
  • Selecting the Proper Indicators
  • Retrieving the Data with Respect to the Indicators
  • Calculating the Importance Weights
  • Calculating the Performance Indices
  • Aggregate Ranking Using Copeland method
  • Calculating the Composite Sustainability Ranking Using Copeland method
  • ALERT MANAGEMENT AGENT
  • Communication Agent
  • DISCUSSION AND IMPLICATIONS
  • CONCLUSION
  • APPENDIX
  • REFERENCES
  • A MODULAR ARTIFICIAL NEURAL NETWORK BASED DECISION MAKING IN A MULTI-AGENT ROBOT SOCCER SYSTEMS
  • ABSTRACT
  • 1. INTRODUCTION 2. THE PROBLEM DESCRIPTION
  • 3. THE BASIC ANN ARCHITECTURE
  • 4. MODULAR ANN ARCHITECTURE
  • 5. RESULTS AND DISCUSSION
  • CONCLUSION
  • REFERENCES
  • SECURITY AND PRIVACY IN TRACK AND TRACE INFRASTRUCTURES
  • ABSTRACT
  • 1. INTRODUCTION
  • 1.1. Radio Frequency Identification
  • 1.2. Track and Trace Infrastructures
  • 2. SECURITY REQUIREMENTS
  • 2.1. Confidentiality
  • 2.2. Integrity
  • 3. BATCH RECALLS
  • 3.1. Example
  • 3.2. Building Blocks
  • 3.2.1. Identity-based Encryption
  • 3.2.2. Boneh-Franklin Encryption

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