Where the Immunological Computation Research is heading?

Speaker:  Dipankar Dasgupta – Memphis, TN, United States
Topic(s):  Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science


The biological immune system exhibits some remarkable properties, including distributed processing, pathogenic pattern recognition, decentralized control, adaptability, diversity, signaling, etc. These properties allow to distinguish self and dangerous non-self, and to quickly recognition and response. The Immunological Computation (IC) field has evolved, also referred as Immuno-computing or Artificial Immune Systems (AIS),  for solving science and engineering problems. In general, some of these models are intended to describe immunological processes for a better understanding of the dynamical behavior of the immune system in the presence of antigens. On the other hand, immunity-based models have been developed in an attempt to solve wide variety of real-world problems. 

In this tutorial, an up-to-date review and progress of IC techniques, particularly, negative selection (NS) algorithms will be presented in details. Accordingly, following its initial model, the fundamental characteristics of a family of NS algorithms and their applications will be discussed. The tutorial will also cover the limitations and applicability issues of NS Algorithms, and how NS relates to danger theory model.

About this Lecture

Number of Slides:  120
Duration:  120 minutes
Languages Available:  English
Last Updated: 

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