| Description |
1 online resource |
| Series |
Computer science, technology and applications |
|
Computer science, technology and applications
|
| Contents |
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 |
| Bibliography |
Includes bibliographical references and index |
| Notes |
English |
|
Description based on print version record |
| Subject |
Intelligent agents (Computer software)
|
|
Distributed artificial intelligence.
|
|
Data mining.
|
|
COMPUTERS -- Enterprise Applications -- Business Intelligence Tools.
|
|
COMPUTERS -- Intelligence (AI) & Semantics.
|
|
Data mining
|
|
Distributed artificial intelligence
|
|
Intelligent agents (Computer software)
|
| Form |
Electronic book
|
| Author |
Bouça, Duarte.
|
|
Gafagnão, Amaro.
|
| LC no. |
2020687707 |
| ISBN |
9781611225761 |
|
1611225760 |
|
