Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges

Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to high complexity, interaction, parallelism and continuous change of roles and organisation between agents. In this paper we record our research experience on formal modelling of MAS. We review our research throughout the last decade, by describing the problems we have encountered and the decisions we have made towards resolving them and providing solutions. Much of this work involved membrane computing and classes of P Systems, such as Tissue and Population P Systems, targeted to the modelling of MAS whose dynamic structure is a prominent characteristic. More particularly, social insects (such as colonies of ants, bees, etc.), biology inspired swarms and systems with emergent behaviour are indicative examples for which we developed formal MAS models. Here, we aim to review our work and disseminate our findings to fellow researchers who might face similar challenges and, furthermore, to discuss important issues for advancing research on the application of membrane computing in MAS modelling.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

Qualitative modelling and analysis of regulations in multi-cellular systems using Petri nets and topological collections

In this paper, we aim at modelling and analyzing the regulation processes in multi-cellular biological systems, in particular tissues. The modelling framework is based on interconnected logical regulatory networks a la Rene Thomas equipped with information about their spatial relationships. The semantics of such models is expressed through colored Petri nets to implement regulation rules, combined with topological collections to implement the spatial information. Some constraints are put on the the representation of spatial information in order to preserve the possibility of an enumerative and exhaustive state space exploration. This paper presents the modelling framework, its semantics, as well as a prototype implementation that allowed preliminary experimentation on some applications.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

An Individual-based Probabilistic Model for Fish Stock Simulation

We define an individual-based probabilistic model of a sole (Solea solea) behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA), a new formalism that is introduced in the paper and that is shown to be interpretable as a Markov decision process. A given EPDTA model can be probabilistically model-checked by giving a suitable translation into syntax accepted by existing model-checkers. In order to simulate the dynamics of a given population of soles in different environmental scenarios, an agent-based simulation environment is defined in which each agent implements the behaviour of the given EPDTA model. By varying the probabilities and the characteristic functions embedded in the EPDTA model it is possible to represent different scenarios and to tune the model itself by comparing the results of the simulations with real data about the sole stock in the North Adriatic sea, available from the recent project SoleMon. The simulator is presented and made available for its adaptation to other species.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

Testing a deterministic implementation against a non-controllable non-deterministic stream X-machine

A stream X-machine is a type of extended finite state machine with an associated development approach that consists of building a system from a set of trusted components. One of the great benefits of using stream X-machines for the purpose of specification is the existence of test generation techniques that produce test suites that are guaranteed to determine correctness as long as certain well-defined conditions hold. One of the conditions that is traditionally assumed to hold is controllability: this insists that all paths through the stream X-machine are feasible. This restrictive condition has recently been weakened for testing from a deterministic stream X-machine. This paper shows how controllability can be replaced by a weaker condition when testing a deterministic system against a non-deterministic stream X-machine. This paper therefore develops a new, more general, test generation algorithm for testing from a non-deterministic stream X-machine

Checking experiments for stream X-machines

This article is a post-print version of the published article which may be accessed at the link below. Copyright © 2010 Elsevier B.V. All rights reserved.Stream X-machines are a state based formalism that has associated with it a particular development process in which a system is built from trusted components. Testing thus essentially checks that these components have been combined in a correct manner and that the orders in which they can occur are consistent with the specification. Importantly, there are test generation methods that return a checking experiment: a test that is guaranteed to determine correctness as long as the implementation under test (IUT) is functionally equivalent to an unknown element of a given fault domain Ψ. Previous work has show how three methods for generating checking experiments from a finite state machine (FSM) can be adapted to testing from a stream X-machine. However, there are many other methods for generating checking experiments from an FSM and these have a variety of benefits that correspond to different testing scenarios. This paper shows how any method for generating a checking experiment from an FSM can be adapted to generate a checking experiment for testing an implementation against a stream X-machine. This is the case whether we are testing to check that the IUT is functionally equivalent to a specification or we are testing to check that every trace (input/output sequence) of the IUT is also a trace of a nondeterministic specification. Interestingly, this holds even if the fault domain Ψ used is not that traditionally associated with testing from a stream X-machine. The results also apply for both deterministic and nondeterministic implementations

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

Towards a P Systems Pseudomonas Quorum Sensing Model

Pseudomonas aeruginosa is an opportunistic bacterium that exploits quorum sensing communication to synchronize individuals in a colony and this leads to an increase in the effectiveness of its virulence. In this paper we derived a mechanistic P systems model to describe the behavior of a single bacterium and we discuss a possible approach, based on an evolutionary algorithm, to tune its parameters that will allow a quantitative simulation of the system.Kingdom's Engineering and Physical Sciences Research Council EP/D021847/

Distributed models in P-Systems architectures to reduce computation time

Membrane systems are computational equivalent to Turing machines. However, their distributed and massively parallel nature obtains polynomial solutions opposite to traditional non-polynomial ones. At this point, it is very important to develop dedicated hardware and software implementations exploiting those two membrane systems features. Dealing with distributed implementations of P systems, the bottleneck communication problem has arisen. When the number of membranes grows up, the network gets congested. The purpose of distributed architectures is to reach a compromise between the massively parallel character of the system and the needed evolution step time to transit from one configuration of the system to the next one, solving the bottleneck communication problem. 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. 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 processors

Towards Probabilistic Model Checking on P Systems Using PRISM

This paper presents the use of P systems and π-calculus to model interacting molecular entities and how they are translated into a probabilistic and symbolic model checker called PRISM.Ministerio de Educación y Ciencia TIN2005-09345-C04-01Junta de Andalucía TIC-58

A Membrane-Inspired Evolutionary Algorithm with a Population P System and its Application to Distribution System Recon guration

This paper develops a membrane-inspired evolutionary algorithm, PSMA, which is designed by using a population P system and a quantum-inspired evolutionary algorithm (QIEA). We use a population P system with three cells to organize three types of QIEAs, where communications between cells are performed at the level of genes, instead of the level of individuals reported in the existing membrane algorithms in the literature. Knapsack problems are applied to discuss the parameter setting and to test the effectiveness of PSMA. Experimental results show that PSMA is superior to four representative QIEAs and our previous work with respect to the quality of solutions and the elapsed time. We also use PSMA to solve the optimal distribution system reconfiguration problem in power systems for minimizing the power loss.Junta de Andalucía P08-TIC-04200Ministerio de Ciencia e Innovación TIN-2009-1319