A new simulation algorithm for multienvironment probabilistic P systems

Multienvironment P systems are the base of a general framework for modeling ecosystems dynamics. On one hand, this modeling framework represents the structural and dynamical aspects of real ecosystems in a discrete, modular and compressive way. On the other hand, the inherent randomness and uncertainty of biological systems are captured by using probabilistic strategies. Nowadays, the simulation of these P systems based models is fundamental for experimentation and validation. In this paper, we introduce a new simulation algorithm, called DNDP, which performs object distribution and maximal consistency in the application of rules, that are crucial aspects of these systems. The paper also depicts a parallel implementation of the algorithm, and a comparison with the existing algorithm in PLinguaCore is provided. In order to test the performance of the presented algorithm, several experiments (simulations) have been carried out over four simple P systems with the same skeleton and different number of environments.