Modelling Dynamic Organization of Biology-Inspired Multi-agent Systems with Communicating X-Machines and Population P Systems

Stamatopoulou, Ioanna; Gheorghe, Marian; Kefalas, Petros

doi:10.1007/978-3-540-31837-8_25

Cited by 14 publications

(10 citation statements)

References 12 publications

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“…Foraging bees communicate the destination of the food source by the famous dance of the returning bee [11]. Similar emergent behaviour but with less direct communication among agents can be achieved in flocks, schools and herds [31,27].…”

Section: Case Studies For Multi-agent Systemsmentioning

confidence: 99%

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

Kefalas

Stamatopoulou

2010

Electron. Proc. Theor. Comput. Sci.

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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

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Section: Case Studies For Multi-agent Systemsmentioning

confidence: 99%

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

Kefalas

Stamatopoulou

2010

Electron. Proc. Theor. Comput. Sci.

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“…These chemical execution models have been applied to diverse fields [21] such as image processing applications, operating systems, compilers, dynamic software reconfiguration [25], multi-agent systems [26] and distributed computing [27]. More recently, γ-calculus has been introduced as a formalism that extends the original Gamma model to a higher-order calculus.…”

Section: Gammamentioning

confidence: 99%

A Metabolic Approach to Protocol Resilience

Tschudin

Yamamoto

2005

Lecture Notes in Computer Science

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Abstract. The goal of this research is to create robust execution circuits for communication software which can distribute over a network and which continues to provide its service despite parts of the implementation being knocked out. Like packets that can be lost (which can be recovered by the appropriate protocols) we envisage an environment where parts of a protocol's execution can be lost. The remaining implementation elements should continue to operate and be able to recover by themselves for restoring full services again. Based on a chemical execution model, we show a few initial examples of packet processing functions that are robust against the knock-out of any single instruction. These examples illustrate how the model can be applied to implement resilient communication protocols, to which we add regulatory signals that can be used to steer the protocols' code basis.

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“…The testing process can therefore be seen as integration testing. The primary interest in stream X-machines has been software development but they have also been used to model biological agents [14][15][16] and NASA has discussed using them in the development of swarm satellite systems [17].…”

Section: Introductionmentioning

confidence: 99%

Checking experiments for stream X-machines

Hierons

2010

Theoretical Computer Science

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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\ud 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\ud X-machine. The results also apply for both deterministic and nondeterministic implementations

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Modelling Dynamic Organization of Biology-Inspired Multi-agent Systems with Communicating X-Machines and Population P Systems

Cited by 14 publications

References 12 publications

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

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

A Metabolic Approach to Protocol Resilience

Checking experiments for stream X-machines

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