Biologically inspired rule-based multiset programming paradigm for soft-computing

This paper describes a rule-based multiset programming paradigm, as a unifying theme for biological, chemical, DNA, physical and molecular computations. The computations are interpreted as the outcome arising out of deterministic, nondeterministic or stochastic interaction among elements in a multiset object space which includes the environment. These interactions are like chemical reactions and the evolution of the multiset can mimic the biological evolution. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of elements, so that the elements evolve toward an equilibrium or an emergent state. Hence, this paradigm is widely applicable; e.g., to conventional algorithms, evolutionary algorithms, Markov chain Monte Carlo based Bayesian inference, genetic algorithms, self-organized criticality and active walker models (swarm and ant intelligence), DNA and molecular computing. Practical realisation of this paradigm is achieved through a coordination programming language using Multiset and transactions. This paradigm permits carrying out parts or all of the computations independently on distinct processors and is eminently suitable for cluster and grid computing.