LNCS 2787 Revisiting the Foundations of Artificial Immune Systems A Problem Oriented Perspective 1st Edition by Alex Freitas, Jon Timmis  ISBN 3540451927 9783540451921

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Product details:

ISBN 10: 3540451927

ISBN 13: 9783540451921

Author:  Alex A. Freitas, Jon Timmis  

LNCS 2787 – Revisiting the Foundations of Artificial Immune Systems: A Problem-Oriented Perspective 1st Edition: 

Since their development, AIS have been used for a number of machine learning tasks including that of classification. Within the literature, there appears to be a lack of appreciation for the possible bias in the selection of various representations and affinity measures that may be introduced when employing AIS in classification tasks. Problems are then compounded when inductive bias of algorithms are not taken into account when applying seemingly generic AIS algorithms to specific application domains. This paper is an attempt at highlighting some of these issues. Using the example of classification, this paper explains the potential pitfalls in representation selection and the use of various affinity measures. Additionally, attention is given to the use of negative selection in classification and it is argued that this may be not an appropriate algorithm for such a task. This paper then presents ideas on avoiding unnecessary mistakes in the choice and design of AIS algorithms and ultimately delivered solutions.

 

LNCS 2787 – Revisiting the Foundations of Artificial Immune Systems: A Problem-Oriented Perspective 1st Edition Table of contents:

1 Introduction

2 An Overview of Data Mining Tasks and Inductive Bias

• 2.1 The Classification Task
• 2.2 The Anomaly Detection Task and Its Relationship to the Classification Task
• 2.3 Inductive Bias

3 Representation Issues

• 3.1 A Brief Review of Instance-Based and Rule-Based Knowledge Representations
• 3.2 A Critical Review of Representation Issues in a Number of Existing Artificial Immune Systems
• 3.3 Antibody Diversity in the Natural Immune System
• 3.4 Lessons To Be Taken From Natural Antibody Diversity for Designing More Adaptive AIS

4 Affinity Issues

• 4.1 A Review of the Importance of Affinity Functions in Artificial Immune Systems
• 4.2 A Critical Review of Affinity Issues in a Number of Existing Artificial Immune Systems

5 Immune Processes for AIS: Clonal Selection and Negative Selection

• 5.1 Clonal Selection
  • 5.1.1 The Clustering of Receptors for Activating Immune Cells and Its Significance for AIS
  • 5.1.2 The Two-Signal Mechanism for Activating Immune Cells and Its Significance for AIS
  • 5.1.3 A Critical Review of the Use of Natural Immune Cell Activation Principles in Existing AIS
• 5.2 Negative Selection

6 Conclusions and Future Research

 

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