Lucie Ciencialová

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.

P colonies and their extensions

P colonies are one of the variants of computational devices based on independent membrane agents, which are evolved and acting in a shared environment. P colonies belong to the family of models of membrane computing called P systems. We show that P colonies with capacity three and two agents using homogeneous programs without checking rules are computationally complete as well as eco-P colonies with two agents and a passive environment and PCol automata working in init mode.

Modularity in p colonies with checking rules

P colony, which was introduced in [9], is an abstract computing device composed of independent agents, acting and evolving in a shared environment. In this paper we bring a new view to investigation of the behavior of the P colonies. The first part of the paper focuses on the modularity of the P colonies with checking rules. We group the agents into modules with specific function. In the second part of the paper we introduce improved results concerning the computational power of the P colonies with capacity one.

Membrane automata with priorities

In this paper the one-way P automata with priorities are introduced. Such automata are P systems where the membranes are only allowed to consume objects from parent membranes, under the given conditions. The result of computation of these systems is the set of multiset sequences consumed by skin membrane into the system. The rules associated in some order with each membrane, cannot modify any objects, they can only move them through membrane. We show that P automata with priorities and two membranes can accept every recursively enumerated language.

P Colonies with Evolving Environment

We study two variants of P colonies with dynamic environment changing due to an underlying 0L scheme: P colonies with two objects inside each agent that can only consume objects, and P colonies with one object inside each agent which uses rewriting and communication rules. We show that the first kind of P colonies with one consumer agent can generate all sets of natural numbers computed by partially blind register machines. The second kind of P colonies with two agents with rewriting/communication rules is computationally complete. Finally, we demonstrate that P colonies with one such agent with checking programs can simulate catalytic P systems with one catalyst, and consequently, another relation to partially blind register machines is established.

2D P colonies

We continue the investigation of P colonies introduced in [4], a class of abstract computing devices composed of independent agents, acting and evolving in a shared environment. We are introducing 2D P colonies with a 2D environment where the agents are located. Agents have limited information about the contents of the environment where they can move in four directions. To present computations of 2D P colonies we construct a simulation environment.

A class of restricted P colonies with string environment

In this paper we continue the study of variants of P colonies, called APCol systems, where the environment is given as a string and the model is an accepting system. We develop the concept by introducing the notion of the generating working mode. We then compare the power of a special subclass of APCol systems working in the generating mode to the power of register machines and context-free matrix grammars without appearance checking.

The Abilities of P Colony Based Models in Robot Control

P colonies were introduced in 2004 (see [10]) as an abstract computing device composed of independent single membrane agents, reactively acting and evolving in a shared environment. Each agent is equipped with a set of rules which are structured into simple programs. There are some models based on from original P colony. In most cases, models are equipped with such components which are associated with the environment. This is the case of Pcol automaton too. The agents work not only with environment but also with an input tape. We use this two theoretical computational devices to build complex robot controllers. In this paper we introduce simple controllers; the first one is used for fulfilling instructions and the other one for passing the maze using right-hand rule. We followed two different approaches and ideas and we present the obtained results in this paper.

P Colonies Processing Strings

In this paper we introduce and study P colonies where the environment is given as a string. These constructs, called automaton-like P colonies or APCol systems, behave like automata: during functioning, the agents change their own states and process the symbols of the string. We show that the family of e-free languages accepted by jumping finite automata is properly included in the family of languages accepted by APCol systems with one agent and any e-free recursively enumerable language can be obtained as a projection of a language accepted by an automaton-like P colony with two agents.

Modelling of Surface Runoff Using 2D PäColonies

We continue the investigation of 2D P colonies introduced as a class of abstract computing devices composed of independent agents, acting and evolving in a shared 2D environment where the agents are located. Agents have limited information about the contents of the environment where they can move in four directions. In this paper we continue the research of modelling surface runoff in 2D P colonies. We have added information about flow direction and amount of water in sinks (places without runoff, lakes,...) to the simulation environment. The data from the simulation is compared with the data generated by simulation model of water erosion SIMWE.