On the Classes of Languages Characterized by Generalized P Colony Automata

We study the computational power of generalized P colony automata and show how it is in uenced by the capacity of the system (the number of objects inside the cells of the colony) and the types of programs which are allowed to be used (restricted and unrestricted com-tape and all-tape programs, or programs allowing any kinds of rules)

P Colony Automata with LL(k)-like Conditions

We investigate the possibility of the deterministic parsing (that is, parsing without backtracking) of languages characterized by (generalized) P colony automata. We de ne a class of P colony automata satisfying a property which resembles the LL(k) property of context-free grammars, and study the possibility of parsing the characterized languages using a k symbol lookahead, as in the LL(k) parsing method for context-free languages

Generalized P Colony Automata and Their Relation to P Automata

We investigate genPCol automata with input mappings that can be realized through the application of finite transducers to the string representations of multisets. We show that using unrestricted programs, these automata characterize the class of recursively enumerable languages. The same holds for systems with all-tape programs, having capacity at least two. In the case of systems with com-tape programs, we show that they characterize language classes which are closely related to those characterized by variants of P automata

Parsing languages of P colony automata

In this paper a subclass of generalized P colony automata is defined that satisfies a property which resembles the LL(k) property of context-free grammars The possibility of parsing the characterized languages using a k symbol lookahead, as in the LL(k) parsing method for context-free languages, is examined

Graph-Transfromational Swarms : A Graph-Transformational Approach to Swarm Computation

Computer systems are becoming increasingly distributed and interconnected. Various emerging notions, such as smart grids, system of systems, industry 4.0 or cyber-physical systems have gained more and more importance during the last few years. All of them propose to solve engineering problems by using several autonomous components that act in parallel and are interconnected, foremost using Internet technologies. These emerging concepts look very promising, but also exhibit various technical challenges. For instance, how is it possible to develop decentralized control mechanisms that produce a desired emerging behavior to solve a given task or how to model such solutions in order to analyze their behavior in terms of complexity and correctness? These are two major questions that this thesis attempts to answer. Indeed, it provides graph-transformational swarms as a novel concept that combines the ideas and principles of swarms and swarm computing and the formal methods of graph transformation to model distributed systems. Graph-transformational swarms captures the advantages of swarms and swarm computing and of graph transformation

Membrane systems with limited parallelism

Membrane computing is an emerging research field that belongs to the more general area of molecular computing, which deals with computational models inspired from bio-molecular processes. Membrane computing aims at defining models, called membrane systems or P systems, which abstract the functioning and structure of the cell. A membrane system consists of a hierarchical arrangement of membranes delimiting regions, which represent various compartments of a cell, and with each region containing bio-chemical elements of various types and having associated evolution rules, which represent bio-chemical processes taking place inside the cell. This work is a continuation of the investigations aiming to bridge membrane computing (where in a compartmental cell-like structure the chemicals to evolve are placed in compartments defined by membranes) and brane calculi (where one considers again a compartmental cell-like structure with the chemicals/proteins placed on the membranes themselves). We use objects both in compartments and on membranes (the latter are called proteins), with the objects from membranes evolving under the control of the proteins. Several possibilities are considered (objects only moved across membranes or also changed during this operation, with the proteins only assisting the move/change or also changing themselves). Somewhat expected, computational universality is obtained for several combinations of such possibilities. We also present a method for solving the NP-complete SAT problem using P systems with proteins on membranes. The SAT problem is solved in O(nm) time, where n is the number of boolean variables and m is the number of clauses for an instance written in conjunctive normal form. Thus, we can say that the solution for each given instance is obtained in linear time. We succeeded in solving SAT by a uniform construction of a deterministic P system which uses rules involving objects in regions, proteins on membranes, and membrane division. Then, we investigate the computational power of P systems with proteins on membranes in some particular cases: when only one protein is placed on a membrane, when the systems have a minimal number of rules, when the computation evolves in accepting or computing mode, etc. This dissertation introduces also another new variant of membrane systems that uses context-free rewriting rules for the evolution of objects placed inside compartments of a cell, and symport rules for communication between membranes. The strings circulate across membranes depending on their membership to regular languages given by means of regular expressions. We prove that these rewriting-symport P systems generate all recursively enumerable languages. We investigate the computational power of these newly introduced P systems for three particular forms of the regular expressions that are used by the symport rules. A characterization of ET0L languages is obtained in this context