Similitudes y diferencias: el Bosco y el Quevedo de los Sueños

Desde Xavier de Salas, pasando por Marimée y Menéndez Pelayo, hasta Luis Astrana Marín y Américo Castro han sido muchos los ilustres que han relacionado ambos artistas. Lo que hace este autor es destacar que tras esa técnica común de acumulación o enumeración caótica, según Leo Spitzer, lo que subyace son dos actitudes opuestas ante sus respectivas sociedades. El Bosco es un pre-erasmista, que perteneció a los «Hermanos de la Vida en Común», y que criticó a los eclesiásticos, al poder, al lucro y a la hipocresía, por un afán de perfección moral. Quevedo es un contra-reformista que llega a decir que «El Estado-Rey debería ser puro gasto y la nobleza su único beneficiario». Logró ser Señor de la Torre, pero siempre se le hizo poco

Simulating Membrane Systems in Digital Computers

* Work partially supported by contribution of EU commission Under The Fifth Framework Programme, project “MolCoNet” IST-2001-32008.Membrane Computing started with the analogy between some processes produced inside the complex structure of living cells and computational processes. In the same way that in other branches of Natural Computing, the model is extracted from nature but it is not clear whether or not the model must come back to nature to be implemented. As in other cases in Natural Computing: Artificial Neural Networks, Genetic Algorithms, etc; the models have been implemented in digital computers. Hence, some papers have been published considering implementation of Membrane Computing in digital computers. This paper introduces an overview in the field of simulation in Membrane Computing

Extended Networks of Evolutionary Processors

This paper presents an extended behavior of networks of evolutionary processors. Usually, such nets are able to solve NP-complete problems working with symbolic information. Information can evolve applying rules and can be communicated though the net provided some constraints are verified. These nets are based on biological behavior of membrane systems, but transformed into a suitable computational model. Only symbolic information is communicated. This paper proposes to communicate evolution rules as well as symbolic information. This idea arises from the DNA structure in living cells, such DNA codes information and operations and it can be sent to other cells. Extended nets could be considered as a superset of networks of evolutionary processors since permitting and forbidden constraints can be written in order to deny rules communication

Polynomial regression using a perceptron with axo-axonic connections

Social behavior is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these network

String Measure Applied to String Self-Organizing Maps and Networks of Evolutionary Processors

* Supported by projects CCG08-UAM TIC-4425-2009 and TEC2007-68065-C03-02This paper shows some ideas about how to incorporate a string learning stage in self-organizing algorithms. T. Kohonen and P. Somervuo have shown that self-organizing maps (SOM) are not restricted to numerical data. This paper proposes a symbolic measure that is used to implement a string self-organizing map based on SOM algorithm. Such measure between two strings is a new string. Computation over strings is performed using a priority relationship among symbols; in this case, symbolic measure is able to generate new symbols. A complementary operation is defined in order to apply such measure to DNA strands. Finally, an algorithm is proposed in order to be able to implement a string self-organizing map

Filtered Networks of Evolutionary Processors

* Supported by INTAS 00-626 and TIC 2003-09319-c03-03.This paper presents some connectionist models that are widely used to solve NP-problems. Most well known numeric models are Neural Networks that are able to approximate any function or classify any pattern set provided numeric information is injected into the net. Neural Nets usually have a supervised or unsupervised learning stage in order to perform desired response. Concerning symbolic information new research area has been developed, inspired by George Paun, called Membrane Systems. A step forward, in a similar Neural Network architecture, was done to obtain Networks of Evolutionary Processors (NEP). A NEP is a set of processors connected by a graph, each processor only deals with symbolic information using rules. In short, objects in processors can evolve and pass through processors until a stable configuration is reach. This paper just shows some ideas about these two models

Differential Evoluiton - Particle Swarm Optimization

This paper shows the Particle Swarm Optimization algorithm with a Differential Evolution. Each candidate solution is sampled uniformly in [!5,5] D, whereDdenotes the search space dimension, and the evolution is performed with a classical PSO algorithm and a classical DE/x/1 algorithm according to a random threshold

Networks of Evolutionary Processors: Java Implementation of a Threaded Processor

This paper is focused on a parallel JAVA implementation of a processor defined in a Network of Evolutionary Processors. Processor description is based on JDom, which provides a complete, Java-based solution for accessing, manipulating, and outputting XML data from Java code. Communication among different processor to obtain a fully functional simulation of a Network of Evolutionary Processors will be treated in future. A safe-thread model of processors performs all parallel operations such as rules and filters. A non-deterministic behavior of processors is achieved with a thread for each rule and for each filter (input and output). Different results of a processor evolution are shown

Circuit FPGA for active rules selection in a transition P system region

P systems or Membrane Computing are a type of a distributed, massively parallel and non deterministic system based on biological membranes. These systems perform a computation through transition between two consecutive configurations. As it is well known in membrane computing, a configuration consists in a m-tuple of multisets present at any moment in the existing m regions of the system at that moment time. Transitions between two configurations are performed by using evolution rules which are in each region of the system in a non-deterministic maximally parallel manner. This article shows the development of a hardware circuit of selection of active rules in a membrane of a transition P-system. This development has been researched by using the Quartus II tool of Altera Semiconductors. In the first place, the initial specifications are defined in orfer to outline the synthesis of the circuit of active rules selection. Later on the design and synthesis of the circuit will be shown, as well as, the operation tests required to present the obtained results

Membrane Dissolution in Distributed Architectures of P-Systems

The goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the main results regarding the way membranes can be placed on processors in order to get a software/hardware simulation of P-Systems in a distributed environment. Secondly, we improve some results about the membrane dissolution problem, prove that it is connected, and discuss the possibility of simulating this property in the distributed model. All this yields an improvement in the system parallelism implementation since it gets an increment of the parallelism of the external communication among processors. Also, the number of processors grows in such a way that is notorious the increment of the parallelism in the application of the evolution rules and the internal communica-tionsstudy because it gets an increment of the parallelism in the application of the evolution rules and the internal communications. Proposed ideas improve previous architectures to tackle the communication bottleneck problem, such as reduction of the total time of an evolution step, increase of the number of membranes that could run on a processor and reduction of the number of processor