Towards a Conceptual Framework for Artificial Immune Systems

S Stepney; R Smith; J Timmis; A Tyrrell

Towards a Conceptual Framework for Artificial Immune Systems

Research output: Contribution to conference › Other

Abstract

We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of AIS network models. We further propose ways to unify several domains into a common meta-framework, in the context of AIS population models. We finally hint at the possibility of a novel instantiation of such a meta-framework, thereby allowing the building of a specific computational framework that is inspired by biology, but not restricted to any one particular biological domain.

Original language	Undefined/Unknown
Pages	53-64
Publication status	Published - 2004

Access to Document

http://www-users.cs.york.ac.uk/~susan/bib/ss/nonstd/icaris04.htm

Cite this

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title = "Towards a Conceptual Framework for Artificial Immune Systems",

abstract = "We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of AIS network models. We further propose ways to unify several domains into a common meta-framework, in the context of AIS population models. We finally hint at the possibility of a novel instantiation of such a meta-framework, thereby allowing the building of a specific computational framework that is inspired by biology, but not restricted to any one particular biological domain.",

author = "S Stepney and R Smith and J Timmis and A Tyrrell",

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T1 - Towards a Conceptual Framework for Artificial Immune Systems

AU - Stepney, S

AU - Smith, R

AU - Timmis, J

AU - Tyrrell, A

PY - 2004

Y1 - 2004

N2 - We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of AIS network models. We further propose ways to unify several domains into a common meta-framework, in the context of AIS population models. We finally hint at the possibility of a novel instantiation of such a meta-framework, thereby allowing the building of a specific computational framework that is inspired by biology, but not restricted to any one particular biological domain.

AB - We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of AIS network models. We further propose ways to unify several domains into a common meta-framework, in the context of AIS population models. We finally hint at the possibility of a novel instantiation of such a meta-framework, thereby allowing the building of a specific computational framework that is inspired by biology, but not restricted to any one particular biological domain.

M3 - Other

SP - 53

EP - 64

ER -