EvoWorkshops 1993, EvoWorkshops 1994: Progress in Evolutionary Computation pp 201-224 | Cite as

The calculus of self-modifiable algorithm based evolutionary computer network routing

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 956)

Abstract

The Calculus of Self-Modifiable Algorithms (CSA) is a universal approach to parallel and intelligent system. Its aim is to integrate different styles of programming and is applied to different areas of future generation computers. Potential applications of CSA include expert systems, machine learning, adaptive systems and many others. The problem of route optimization in computer networks is identified as a task that requires some sort of cost-driven solution that allows for the computation of paths in a network based on experience and inference. The Calculus of Self-Modifiable Algorithm is used to do the specification of this problem by modeling a system of machine learning algorithms that learn proper routing techniques for a particular computer network by incorporating an apportionment of credit system and various rule discovery concepts similar to the learning techniques used in evolutionary computing and symbolic learning.

Keywords

Classifier System Inference Engine Outgoing Link Rule Discovery Route Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  1. 1.Jodrey School of Computer ScienceAcadia University WolfvilleNova ScotiaCanada

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