Rete Algorithm for P System Simulators

The Rete algorithm is a well-known algorithm in rule-based production systems which builds directed acyclic graphs that represent higher-level rule sets. This allows the rule-based systems to avoid complete re-evaluation of all conditions of the rules each step in order to check the applicability of the rules and, therefore, the computational e ciency of the production systems is improved. In this paper we study how these ideas can be applied in the improvement of the design of computational simulators in the framework of Membrane Computing.Junta de Andalucía P08-TIC-04200Ministerio de Economía y Competitividad TIN2012-3743

Semantics of Deductive Databases in a Membrane Computing Connectionist Model

The integration of symbolic reasoning systems based on logic and connectionist systems based on the functioning of living neurons is a vivid research area in computer science. In the literature, one can found many e orts where di erent reasoning systems based on di erent logics are linked to classic arti cial neural networks. In this paper, we study the relation between the semantics of reasoning systems based on propositional logic and the connectionist model in the framework of membrane computing, namely, spiking neural P systems. We prove that the xed point semantics of deductive databases and the immediate consequence operator can be implemented in the spiking neural P systems model

Semantics of Deductive Databases in a Membrane Computing Connectionist Model

The integration of symbolic reasoning systems based on logic and connectionist systems based on the functioning of living neurons is a vivid research area in computer science. In the literature, one can found many e orts where di erent reasoning systems based on di erent logics are linked to classic arti cial neural networks. In this paper, we study the relation between the semantics of reasoning systems based on propositional logic and the connectionist model in the framework of membrane computing, namely, spiking neural P systems. We prove that the xed point semantics of deductive databases and the immediate consequence operator can be implemented in the spiking neural P systems model

Semantics of deductive databases with spiking neural P systems

The integration of symbolic reasoning systems based on logic and connectionist systems based on thefunctioning of living neurons is a vivid research area in computer science. In the literature, one can findmany efforts where different reasoning systems based on different logics are linked to classic artificialneural networks. In this paper, we study the relation between the semantics of reasoning systems basedon propositional logic and the connectionist model in the framework of membrane computing, namely,spiking neural P systems. We prove that the fixed point semantics of deductive databases without nega- tion can be implemented in the spiking neural P systems model and such a model can also deal withnegation if it is endowed with anti-spikes and annihilation rules

Deductive databases and P systems

In computational processes based on backwards chaining, a rule of the type A Ã B1; : : : ;Bn is seen as a procedure which points that the problem A can be split into the problems B1; : : : ;Bn. In classical devices, the subproblems B1; : : : ;Bn are solved sequentially. In this paper we present some questions that circulated during the Second Brainstorming Week related to the application of the parallelism of P systems to computation based on backwards chaining, and we illustrate them with the example of inferential deductive process.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0