LEADER 05255nam 2200673Ia 450 001 9910971301703321 005 20251116221026.0 010 $a1-61122-576-0 035 $a(CKB)2560000000067797 035 $a(EBL)3018147 035 $a(SSID)ssj0000411452 035 $a(PQKBManifestationID)11279108 035 $a(PQKBTitleCode)TC0000411452 035 $a(PQKBWorkID)10354686 035 $a(PQKB)10427156 035 $a(MiAaPQ)EBC3018147 035 $a(Au-PeEL)EBL3018147 035 $a(CaPaEBR)ebr10659069 035 $a(OCoLC)923657260 035 $a(BIP)27953325 035 $a(EXLCZ)992560000000067797 100 $a20091006d2010 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aAgent-based computing /$fDuarte Bouca and Amaro Gafagnao, editors 205 $a1st ed. 210 $aNew York $cNova Science Publishers$dc2010 215 $a1 online resource (348 p.) 225 0 $aComputer science, technology and applications 300 $aDescription based upon print version of record. 311 08$a1-60876-684-5 320 $aIncludes bibliographical references and index. 327 $a""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"" 327 $a""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 "" 327 $a""3.2.2. Feature Selection Experiments""""3.3. 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 "" 327 $a""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 "" 327 $a""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 "" 327 $a""3.2.3. Boneh-Boyen-Goh Encryption "" 330 $aMulti-agent systems often deal with complex applications that require distributed problem solving. In many applications, the individual and collective behaviour of the agents depends on the observed data from distributed sources. This book discusses research issues concerned with the use of multi-agent systems for data mining. 410 0$aComputer Science, Technology and Applications 606 $aIntelligent agents (Computer software) 606 $aDistributed artificial intelligence 606 $aData mining 615 0$aIntelligent agents (Computer software) 615 0$aDistributed artificial intelligence. 615 0$aData mining. 676 $a006.3 701 $aBouc?a$b Duarte$01869543 701 $aGafagna?o$b Amaro$01869544 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910971301703321 996 $aAgent-based computing$94477718 997 $aUNINA