PUMA
Istituto di Scienze Marine     
Buti F., Corradini F., Merelli E., Paschini E., Penna P., Tesei L. An Individual-based Probabilistic Model for Fish Stock Simulation. In: EPTCS: Electronic Proceedings in Theoretical Computer Science, vol. 33 pp. 37 - 55. Proceedings First Workshop on Applications of Membrane computing, Concurrency and Agent-based modelling in POPulation biology - AMCA-POP 2010 (Jena, Germany, 25th August 2010). P. Milazzo, M.J. Pérez Jiménez (eds.). Pro Business Verlag, 2010.
 
 
Abstract
(English)
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.
DOI: 10.4204/EPTCS.33.3
Subject agent-based modelling
agent-based simulation
concurrency
applications of membrane computing
population biology


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