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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Mohr, Philipp H.; Ryan, Nick S.; Timmis, Jon (2004)
Publisher: Springer
Languages: English
Types: Unknown
Subjects: QA76

Classified by OpenAIRE into

mesheuropmc: biochemical phenomena, metabolism, and nutrition
ACM Ref: TheoryofComputation_MISCELLANEOUS
Identifiers:doi:10.1007/b100486
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.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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