Probabilistic parallel programming based on multiset transformation

Murthy, V. K. ; Krishnamurthy, E. V. (1995) Probabilistic parallel programming based on multiset transformation Future Generation Computer Systems, 11 (3). pp. 283-293. ISSN 0167-739X

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Official URL: http://linkinghub.elsevier.com/retrieve/pii/016773...

Related URL: http://dx.doi.org/10.1016/0167-739X(94)00068-P

Abstract

The GAMMA parallel programming model is based on the multiset datastructure. Here, a succession of chemical reactions consume the elements of the multiset and produce new elements according to specific rules, This paper extends GAMMA model to its probabilistic version - called P-GAMMA model to realise evolutionary computations - namely probabilistic, classifier, bucket-brigade learning and genetic algorithms. We also explain how to support evolutionary computations through randomized choices and concurrent transformations on persistent globally accessible tuplespaces using query processing and transaction mechanisms.

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
Keywords:Parallel Programming; Multiset Transformation; GAMMA
ID Code:28142
Deposited On:14 Dec 2010 08:14
Last Modified:04 Jun 2011 06:51

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