Probabilistic parallel programming based on multiset transformation

On fuzzy multiset regular languages

“…In 1989, Blizard [4] introduced the concept of multiset, which is a collection of elements in which elements may occur more than once, is a generalization of a set. In recent years, multiset processing has appeared frequently in various areas of mathematics, computer science, biology and biochemistry (cf., [3,5,21,23,31]). The researchers have also used the concept of multisets in automata theory and introduced the concepts of multiset finite automata and multiset languages (cf., [6,10,11,12]), which play an important role in various areas of theoretical computer science, as in membrane computing.…”

Simulating Complex Dynamical Systems in a Distributed Programming Environment

“…It includes a few unspecified data types and procedures that vary from one application to another. Hence, this Unified Multiset Simulation Paradigm (UMSP) can be used for all conventional algorithms [15], Tabu search, Markov chain Monte Carlo (MCMC), Particle Filters [6], Evolutionary algorithms-classifier systems, bucket brigade learning , Genetic algorithms and Programming [14], Immunocomputing, Self-organized criticality [4] and Active Walker models (ants with scent or multiwalkerparadigm where each walker can influence the other through a shared landscape based on probabilistic selection [9], and Biomimicry [16]. Also it is applicable to non-equilibrium systems using oscillatory mechanisms involving catalytic reactionsas for example of producing ATP (Adenosine triphosphate) from ATP [8].…”

Scalable performance in workstation cluster: influence of a programming paradigm

“…The Gamma model can be extended to include probabilistic choice, Murthy and Krishnamurthy [13]: such an extension is motivated by the theory of evolutionary computations based on probabilistic selection, and also the belief that probabilistic algorithms may speed up computation . The extended model could therefore provide a paradigm for designing a wide variety of programs for classifier systems, probabilistic, bucket brigade learning and the genetic algorithms.…”

“…The Gamma programming paradigm is based on the chemical reaction model, in which the datastructure is a multiset (Banatre et al [1], [2], Murthy and Krishnamurthy [13] ; the computations are interpreted as a succession of chemical reactions consuming the elements of the multiset and producing new elements according to specific rules. The multiset provides a rich datastructure for handling heterogeneous complex programming problems.…”