Catálogo de publicaciones - libros

L systems have been widely used to model and graphically represent the growth of higher plants [20]. In this paper we continue developing the framework introduced in [21], which make use of the topology of membrane structures to model the morphology of branching structures.

In this work we propose an error-correcting approach to solve the identification of P rules for membrane modifications based on the behavior of the P system. To this aim, we take the framework of inductive inference from (structural) positive examples. The algorithm that we propose is based on previous definitions of distances between membrane structures and multiset tree automata.

The paper introduces (purely communicative) tissue P systems with conditional uniport. Conditional uniport means that rules move only one object at a time, but this may be with the help of another one acting as an activator which is left untouched in the place where it is. Tissue P systems with conditional uniport are shown to be computationally complete in the sense that they can recognize all recursively enumerable sets of natural numbers. This is achieved by simulating deterministic register machines.

In this paper we present an analysis of the similarities between distributed evolutionary algorithms and membrane systems. The correspondences between evolutionary operators and evolution rules and between communication topologies and policies in distributed evolutionary algorithms and membrane structures and communication rules in membrane systems are identified. As a result of this analysis we propose new strategies of applying the operators in evolutionary algorithms and new variants of distributed evolutionary algorithms. The behavior of these variants is numerically tested for some continuous optimization problems.