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
Full text not available from this repository.
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 |
Repository Staff Only: item control page
