Ludek Cienciala

On the number of agents in P colonies

We continue the investigation of P colonies introduced in [8], a class of abstract computing devices composed of independent membrane agents, acting and evolving in a shared environment. We decrease the number of agents sufficient to guarantee computational completeness of P colonies with one and with two objects inside each agent, respectively, owing some special restrictions to the type of programs. We characterize the generative power of the partially blind machine by the generative power of special P colonies.

A limitation of cell division in tissue P systems by PSPACE

P systems are abstract distributed computing models inspired by the information flows in living cells and their networks, with applications, e.g., in systems biology and optimization. A tissue P system is a variant based on the interchange of objects between cells due to an underlying communication graph. The model is further enriched with the operation of cell division. This operation allows to produce an exponential number of cells in polynomial time. The paper studies the computational power of polynomially uniform families of these systems. Previous studies demonstrated that they can cover problems ranging between P and NP � co-NP due to the length of communication rules, thus characterizing a borderline between tractability and intractability. We show that, in spite of the exponential space the model can use, the problems solvable by these families in polynomial time lie within the class PSPACE.

About Models Derived from Colonies

There are many different theoretical computational models, where mutually independent agents interfere in a shared environment or they interact with it directly.

P Colonies of Capacity One and Modularity

In this paper, the authors continue the investigation of P colonies introduced in Kelemen, KelemenovAi, and Paun (2004). This paper examines a class of abstract computing devices composed of independent agents, acting and evolving in a shared environment. The first part is devoted to the P colonies of the capacity one. The authors present improved results concerning the computational power of the P colonies with capacity one and without using checking programs. The second part of the paper examines the modularity of the P colonies. The authors then divide the agents into modules.

ON THE POWER OF FAMILIES OF RECOGNIZER SPIKING NEURAL P SYSTEMS

The paper summarizes recent knowledge about computational power of spiking neural P systems and presents a sequence of new more general results. The concepts of recognizer SN P systems and of uniform families of SN P systems provide a formal framework for this study. We establish the relation of computational power of spiking neural P systems with various limitations to standard complexity classes like P, NP, PSPACE and P/poly.