Advertisement

Process Ordering in a Process Calculus for Spatially-Explicit Ecological Models

  • Anna Philippou
  • Mauricio Toro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8368)

Abstract

In this paper we extend palps, a process calculus proposed for the spatially-explicit individual-based modeling of ecological systems, with the notion of a policy. A policy is an entity for specifying orderings between the different activities within a system. It is defined externally to a palps model as a partial order which prescribes the precedence order between the activities of the individuals of which the model is comprised. The motivation for introducing policies is twofold: one the one hand, policies can help to reduce the state-space of a model; on the other hand, they are useful for exploring the behavior of an ecosystem under different assumptions on the ordering of events within the system. To take account of policies, we refine the semantics of palps via a transition relation which prunes away executions that do not respect the defined policy. Furthermore, we propose a translation of palps into the probabilistic model checker prism. We illustrate our framework by applying prism on palps models with policies for conducting simulation and reachability analysis.

References

  1. 1.
    Online PRISM documentation. http://www.prismmodelchecker.org/doc/
  2. 2.
    Barbuti, R., Maggiolo-Schettini, A., Milazzo, P., Pardini, G.: Spatial calculus of looping sequences. Theoret. Comput. Sci. 412(43), 5976–6001 (2011)CrossRefzbMATHMathSciNetGoogle Scholar
  3. 3.
    Barbuti, R., Maggiolo-Schettini, A., Milazzo, P., Troina, A.: A calculus of looping sequences for modelling microbiological systems. Fund. Inf. 72(1–3), 21–35 (2006)zbMATHMathSciNetGoogle Scholar
  4. 4.
    Berec, L.: Techniques of spatially-explicit individual-based models: construction, simulation, and mean-field analysis. Ecol. Model. 150, 55–81 (2002)CrossRefGoogle Scholar
  5. 5.
    Besozzi, D., Cazzaniga, P., Pescini, D., Mauri, G.: Modelling metapopulations with stochastic membrane systems. BioSystems 91(3), 499–514 (2008)CrossRefGoogle Scholar
  6. 6.
    Bioglio, L., Calcagno, C., Coppo, M., Damiani, F., Sciacca, E., Spinella, S., Troina, A.: A Spatial Calculus of Wrapped Compartments. CoRR, abs/1108.3426 (2011)Google Scholar
  7. 7.
    Cardona, M., Colomer, M.A., Margalida, A., Palau, A., Pérez-Hurtado, I., Pérez-Jiménez, M.J., Sanuy, D.: A computational modeling for real ecosystems based on P systems. Nat. Comput. 10(1), 39–53 (2011)CrossRefzbMATHMathSciNetGoogle Scholar
  8. 8.
    Chen, Q., Ye, F., Li, W.: Cellular-automata-based ecological and ecohydraulics modelling. J. Hydroinf. 11(3/4), 252–272 (2009)CrossRefGoogle Scholar
  9. 9.
    Ciocchetta, F., Hillston, J.: Bio-PEPA: a framework for the modelling and analysis of biological systems. Theoret. Comput. Sci. 410(33–34), 3065–3084 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
  10. 10.
    Cleaveland, R., Lüttgen, G., Natarajan, V.: Priority in process algebras. Technical report, Langley Research Center, NASA, USA (1999)Google Scholar
  11. 11.
    Drábik, P., Maggiolo-Schettini, A., Milazzo, P.: Modular verification of interactive systems with an application to biology. Sci. Ann. Comp. Sci. 21(1), 39–72 (2011)Google Scholar
  12. 12.
    Gerber, L.R., VanBlaricom, G.R.: Implications of three viability models for the conservation status of the western population of Steller sea lions (Eumetopias jubatus). Biol. Conserv. 102, 261–269 (2001)CrossRefGoogle Scholar
  13. 13.
    Hoare, C.A.R.: Communicating Sequential Processes. Prentice-Hall, Upper Saddle River (1985)zbMATHGoogle Scholar
  14. 14.
    McCaig, C., Fenton, A., Graham, A., Shankland, C., Norman, R.: Using process algebra to develop predator–prey models of within-host parasite dynamics. J. Theor. Biol. 329, 74–81 (2013)CrossRefMathSciNetGoogle Scholar
  15. 15.
    McCaig, C., Norman, R., Shankland, C.: Process algebra models of population dynamics. In: Horimoto, K., Regensburger, G., Rosenkranz, M., Yoshida, H. (eds.) AB 2008. LNCS, vol. 5147, pp. 139–155. Springer, Heidelberg (2008)Google Scholar
  16. 16.
    McCaig, C., Norman, R., Shankland, C.: From individuals to populations: a mean field semantics for process algebra. Theoret. Comput. Sci. 412(17), 1557–1580 (2011)CrossRefzbMATHMathSciNetGoogle Scholar
  17. 17.
    Milner, R.: A Calculus of Communicating Systems. Springer, Heidelberg (1980)CrossRefzbMATHGoogle Scholar
  18. 18.
    Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes, parts 1 and 2. Inf. Comput. 100, 1–77 (1992)CrossRefzbMATHMathSciNetGoogle Scholar
  19. 19.
    Norman, G., Palamidessi, C., Parker, D., Wu, P.: Model checking probabilistic and stochastic extensions of the \(\pi \)-calculus. IEEE Trans. Softw. Eng. 35(2), 209–223 (2009)CrossRefGoogle Scholar
  20. 20.
    Pardini, G.: Formal modelling and simulation of biological systems with spatiality. Ph.D thesis, University of Pisa (2011)Google Scholar
  21. 21.
    Pearson, R.G., Dawson, T.P.: Long-distance plant dispersal and habitat fragmentation: identifying conservation targets for spatial landscape planning under climate change. Biol. Conserv. 123, 389–401 (2005)CrossRefGoogle Scholar
  22. 22.
    Pescini, D., Besozzi, D., Mauri, G., Zandron, C.: Dynamical probabilistic P-systems. J. Found. Comput. Sci. 17(1), 183–204 (2006)CrossRefzbMATHMathSciNetGoogle Scholar
  23. 23.
    Philippou, A., Toro, M.: Process ordering in a process calculus for spatially-explicit ecological models. Technical report, Department of Computer Science, University of Cyprus, 2013. http://www.cs.ucy.ac.cy/~annap/pt-tr.pdf
  24. 24.
    Philippou, A., Toro, M., Antonaki, M.: Simulation and verification for a process calculus for spatially-explicit ecological models. Sci. Ann. Comput. Sci. 23(1), 119–167 (2013)CrossRefMathSciNetGoogle Scholar
  25. 25.
    Păun, G.: Computing with membranes (P systems): an introduction. In: Rozenberg, G., Salomaa, A. (eds.) Current Trends in Theoretical Computer Science, pp. 845–866. World Scientific, Singapore (2001)Google Scholar
  26. 26.
    Regev, A., Panina, E.M., Silverman, W., Cardelli, L., Shapiro, E.: BioAmbients: an abstraction for biological compartments. Theoret. Comput. Sci. 325(1), 141–167 (2004)CrossRefzbMATHMathSciNetGoogle Scholar
  27. 27.
    Ruxton, G.D., Saravia, L.A.: The need for biological realism in the updating of cellular automata models. Ecol. Model. 107, 105–112 (1998)CrossRefGoogle Scholar
  28. 28.
    Sumpter, D.J.T., Broomhead, D.S.: Relating individual behaviour to population dynamics. Proc. Roy. Soc. B: Biol. Sci. 268(1470), 925–932 (2001)CrossRefGoogle Scholar
  29. 29.
    Tofts, C.: Processes with probabilities, priority and time. Formal Aspects Comput. 6, 536–564 (1994)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of CyprusNicosiaCyprus

Personalised recommendations