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Artificial Immune Systems and Their Applications [Kõva köide]

  • Formaat: Hardback, 323 pages, Illustrations
  • Ilmumisaeg: 29-Jun-1998
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540643907
  • ISBN-13: 9783540643906
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  • Formaat: Hardback, 323 pages, Illustrations
  • Ilmumisaeg: 29-Jun-1998
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540643907
  • ISBN-13: 9783540643906
Teised raamatud teemal:
Artificial immune systems are highly distributed systems based on the principles of the natural system. This is a new and rapidly growing field offering powerful and robust information processing capabilities for solving complex problems. Like artificial neural networks, artificial immune systems can learn new information, recall previously learned information, and perform pattern recognition in a highly decentralized fashion. This volume provides an overview of the immune system from the computational viewpoint. It discusses computational models of the immune system and their applications, and provides a wealth of insights on immunological memory and the effects of viruses in immune response. It will be of professional interest to scientists, academics, vaccine designers, and practitioners.
Part I. Introduction 3(44) An Overview of Artificial Immune Systems and Their Applications 3(19) Dipankar Dasgupta 1 Introduction 3(2) 2 Computational Aspects of the Immune System 5(1) 3 The Nervous System and the Immune System 6(1) 4 Immune System Based Models 7(5) 5 Some Applications of Artificial Immune Systems 12(5) 6 Summary 17(1) References 18(4) The Endogenous Double Plasticity of the Immune Network and the Inspiration to be Drawn for Engineering Artifacts 22(25) Hugues Bersini 1 Introduction 22(6) 2 An Elementary Immune Network and the Basic Principles to be Obeyed by a Double Plastic Adaptive System 28(2) 3 The Endogenous Double Plasticity in Neural Net Classifiers 30(4) 4 The Endogenous Double Plasticity in Autonomous Agents Learning by Reinforcement 34(4) 5 The Endogenous Double Plasticity for the Control of Chaos 38(2) 6 Conclusions 40(1) References 41(6) Part II. Artificial Immune Systems: Modeling & Simulation 47(110) The Central and the Peripheral Immune Systems: What is the Relationship? 47(18) John Stewart Jorge Carneiro 1 Introduction 47(1) 2 Second Generation Network Models 48(7) 3 An Immune Network Incorporating B-T Cell Co-operation 55(4) 4 Concluding Remarks 59(2) References 61(4) Immunology Viewed as the Study of an Autonomous Decentralized System 65(24) Lee A. Segel Ruth Lev Bar-Or 1 Introduction 65(1) 2 A Nano-course in Immunology 65(2) 3 Overall Characterization of the Immune System 67(1) 4 Postulating a Role for Feedback 67(2) 5 Optimizing Effector Performance 69(5) 6 Optimizing Effector Choice 74(5) 7 The Importance of Geography 79(1) 8 Communication 80(1) 9 A Brief Comparison to Some Other Approaches to Decentralized Systems 80(3) 10 Overview 83(3) References 86(3) Immune Network: An Example of Complex Adaptive Systems 89(16) Debashish Chowdhury 1 Introduction 89(1) 2 A Brief Summary of Experimental Phenomena to be Modelled Theoretically 90(2) 3 Clonal Selection and Its Mathematical Modelling 92(6) 4 Beyond Clonal Selection; Immune Network 98(3) 5 Summary and Conclusion 101(1) References 102(3) Immunological Memory is Associative 105(10) Derek J. Smith Stephanie Forrest Alan S. Perelson 1 Introduction 105(1) 2 Immunological Memory 106(2) 3 Sparse Distributed Memory (SDM) 108(1) 4 Correspondence between Immunological Memory and SDM 109(2) 5 Aspects of Associative Recall in the Immune Response 111(1) 6 Summary 112(1) References 112(3) Estimating and Predicting the Number of Free HIV and T Cells by Nonlinear Kalman Filter 115(29) Wai-Yuan Tan Zhihua Xiang 1 Introduction 115(1) 2 A Stochastic Model of the HIV Pathogenesis 116(7) 3 A State Space Model for the HIV Pathogenesis 123(7) 4 An Illustrative Example 130(3) 5 Some Monte Carlo Studies 133(2) 6 Conclusion and Discussion 135(3) References 138(6) Modeling the Effects of Prior Infection on Vaccine Efficacy 144(13) Derek J. Smith Stephanie Forrest David H. Ackley Alan S. Perelson 1 Introduction 144(1) 2 Materials and Methods 145(3) 3 Results and Discussion 148(4) References 152(5) Part III. Artificial Immune Systems: Applications 157(134) Jisys: The Development of an Artificial Immune System for Real World Applications 157(30) John Hunt Jon Timmis Denise Cooke Mark Neal Clive King 1 Introduction 157(1) 2 Research into ISYS 158(5) 3 The JISYS System 163(12) 4 Jisys System Structure 175(2) 5 The Mortgage Fraud Application 177(2) 6 Analysis of JISYS 179(1) 7 Comparison with Related Work 180(1) 8 Future Work 181(3) 9 Conclusions 184(1) References 184(3) Decentralized Behavior Arbitration Mechanism for Autonomous Mobile Robot Using Immune Network 187(23) Yuji Watanabe Akio Ishiguro Yoshiki Uchikawa 1 Introduction 187(2) 2 Biological Immune System 189(2) 3 Proposed Behavior Arbitration Mechanism Based on the Immune System 191(6) 4 Adaptation Mechanisms 197(9) 5 Conclusions and Further Work 206(1) References 207(3) Parallel Search for Multi-Modal Function Optimization with Diversity and Learning of Immune Algorithm 210(11) Toyoo Fukuda Kazuyuki Mori Makoto Tsukiyama 1 Introduction 210(1) 2 Immune Algorithm 211(5) 3 Experiments and Implementation Details 216(3) 4 Conclusion 219(1) References 219(2) Immunized Adaptive Critic for an Autonomous Aircraft Control Application 221(21) Kalmanje KrishnaKumar James Neidhoefer 1 Introduction 221(1) 2 Levels of Intelligent Control 222(2) 3 The Autonomous Aircraft Control Problem 224(3) 4 Immunized Computational Systems 227(4) 5 Immunized Adaptive Critics 231(6) 6 Conclusion 237(3) References 240(2) Blueprint for a Computer Immune System 242(20) Jeffrey O. Kephart Gregory B. Sorkin Morton Swimmer Steve R. White 1 Introduction 242(2) 2 Requirements for a Computer Immune System 244(2) 3 Implementing an Immune System for Cyberspace 246(10) 4 Evaluation and Final Remarks 256(3) References 259(3) An Anomaly Detection Algorithm Inspired by the Immune System 262(16) Dipankar Dasgupta Stephanie Forrest 1 Introduction 262(1) 2 A Negative Selection Algorithm 263(1) 3 Anomaly Detection 264(3) 4 Experiments 267(6) 5 Conclusions 273(2) References 275(3) Immunity-Based Management System for a Semiconductor Production Line 278(13) Toyoo Fukuda Kazuyuki Mori Makoto Tsukiyama 1 Introduction 278(1) 2 Problem of Semiconductor Production System 279(2) 3 Immunity-Based System and Multi-Agent Nets 281(6) 4 Conclusion 287(1) References 288(3) Indexed Bibliography 291(12) Author Index 303(1) Subject Index 304