Generalized Communicating P Systems Working in Fair Sequential Model

In this article we consider a new derivation mode for generalized communicating P systems (GCPS) corresponding to the functioning of population protocols (PP) and based on the sequential derivation mode and a fairness condition. We show that PP can be seen as a particular variant of GCPS. We also consider a particular stochastic evolution satisfying the fairness condition and obtain that it corresponds to the run of a Gillespie's SSA. This permits to further describe the dynamics of GCPS by a system of ODEs when the population size goes to the infinity.Comment: Presented at MeCBIC 201

On a workflow model based on generalized communicating P systems

This paper introduces a new formal mathematical model for investigating workflows from dynamical and behavioural point of view. The model is designed on the basis of a special variant of the biology-inspired formal computational model called membrane systems, where the jobs or services are represented by membrane objects whose behaviour is defined by communication and generalization rules. The model supports running computations in a massive parallel manner, which makes it ideal to model high throughput workflow interpreters. Among the variants introduced in the literature, we have selected the Generalized Communicating P Systems, as it focuses on the communication among the membranes.Most of the workflow languages, based on different formal models like Petri nets or Communicating Sequential Processes, support several predefined structures – namely workflow patterns – to control the workflow interpretation such as conditions, loops etc. In this paper we show how these patterns are adapted into the membrane environment which, taking into account that membrane systems can be used to study complex dynamic systems’ runtime behaviour, makes this model a relevant alternative for the current model

Computationally Complete Generalized Communicating P Systems with Three Cells

International audienc

Isochronal synchrony and bidirectional communication with delay-coupled nonlinear oscillators

We propose a basic mechanism for isochronal synchrony and communication with mutually delay-coupled chaotic systems. We show that two Ikeda ring oscillators (IROs), mutually coupled with a propagation delay, synchronize isochronally when both are symmetrically driven by a third Ikeda oscillator. This synchronous operation, unstable in the two delay-coupled oscillators alone, facilitates simultaneous, bidirectional communication of messages with chaotic carrier waveforms. This approach to combine both bidirectional and unidirectional coupling represents an application of generalized synchronization using a mediating drive signal for a spatially distributed and internally synchronized multi-component system

Exact BER Calculation of Asynchronous DS-CDMA Systems Communicating over Hoyt Channels

An asynchronous binary DS-CDMA system using random spreading sequences is considered in flat Hoyt fading channels. A new closed-form expression is derived for the conditional characteristic function of the multiple access interference. The exact average BER is expressed as a single numerical integration based on the characteristic function approach. The numerical results obtained from our exact BER analysis are verified by our simulation results and also compared to those obtained by the standard Gaussian approximation

Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking

This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications

Towards Efficient Abstractions for Concurrent Consensus

Consensus is an often occurring problem in concurrent and distributed programming. We present a programming language with simple semantics and build-in support for consensus in the form of communicating transactions. We motivate the need for such a construct with a characteristic example of generalized consensus which can be naturally encoded in our language. We then focus on the challenges in achieving an implementation that can efficiently run such programs. We setup an architecture to evaluate different implementation alternatives and use it to experimentally evaluate runtime heuristics. This is the basis for a research project on realistic programming language support for consensus.Comment: 15 pages, 5 figures, symposium: TFP 201