Document details for 'MELA: Modelling in Ecology with Location Attributes'

Authors Vissat, L.L., Hillston, J., Marion, G. and Smith, M.J.
Publication details In "International Workshop on Quantitative Aspects of Programming Languages and Systems (QAPL'16)", 82-97. Eds. Mirco Tribastone and Herbert Wiklicky. Electronic Proceedings in Theoretical Computer Science 227.
Publisher details Electronic Proceedings in Theoretical Computer Science 227
Abstract Ecology studies the interactions between individuals, species and the environment. The ability to predict the dynamics of ecological systems would support the design and monitoring of control strategies and would help to address pressing global environmental issues. It is also important to plan for efficient use of natural resources and maintenance of critical ecosystem services. The mathematical modelling of ecological systems often includes nontrivial specifications of processes that influence the birth, death, development and movement of individuals in the environment, that take into account both biotic and abiotic interactions. To assist in the specification of such models, we introduce MELA, a process algebra for Modelling in Ecology with Location Attributes. Process algebras allow the modeller to describe concurrent systems in a high-level language. A key feature of concurrent systems is that they are composed of agents that can progress simultaneously but also interact - a good match to ecological systems. MELA aims to provide ecologists with a straightforward yet flexible tool for modelling ecological systems, with particular emphasis on the description of space and the environment. Here we present four example MELA models, illustrating the different spatial arrangements which can be accommodated and demonstrating the use of MELA in epidemiological and predator-prey scenarios.
Last updated 2018-03-02
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