From: Kris Ganjam (krisgan@microsoft.com)
Date: Fri Sep 08 2000 - 17:51:33 PDT
AIS research has been ruminating for the past several years, but I only just
stumbled on it while grazing in the Redmond Barnes & Noble. These
algorithms have been applied to pattern recognition, multi-agent systems and
(to perhaps take a metaphor too far) even anti-virus software.
-Kris
http://www.cs.ucl.ac.uk/staff/J.Kim/ComputerImmune.html
http://www.msci.memphis.edu/~dasgupta/ais-book.html
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.
From an information-processing perspective, the immune system is a
remarkable parallel and distributed adaptive system. It uses learning,
memory, and associative retrieval to solve recognition and classification
tasks. In particular, it learns to recognize relevant patterns, remember
patterns that have been seen previously, and use combinatorics to construct
pattern detectors efficiently. Also, the overall behavior of the system is
an emergent property of many local interactions. These remarkable
information-processing abilities of the immune system provide several
important aspects in the field of computation. Artificial Immune Systems are
used in pattern recognition, fault detection, computer security, and a
variety of other applications researchers are exploring in the field of
science and engineering.
* Computational methods based on Immunological principles
* Artificial Immune systems for Pattern Recognition
* Immunity-based system for Anomaly or fault detection
* Immune Network Models and their applications
* Immunity-based system as a multi-agent system
* Multi-agent approach for modeling and simulating immune systems
* Immunity-based systems for self-diagnosis and self-organization
* Immunity-based approach for collective intelligence
* Immunity-based systems for optimization and search
* The immune system as a prototype of Autonomous Decentralized Systems
* Immunity-based approach for Artificial Life
* Immunity-based approach for security of information systems
* Immunological approach against computer viruses and internet worms
* The immune system as a metaphor for computer based learning systems
* Immunity-based systems as a distributed learning system
* Immunological Computation for data mining
* Immunity-based Cognitive Models
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