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EcoPS: a particle swarm algorithm to model group-foraging

Published: 07 July 2007 Publication History

Abstract

Recent work has introduced a simulation model of ecological processes in terms of a very simple Particle Swarm algorithm. This abstract model produced qualitatively realistic behaviours, but do these results hold up in a model constrained by more plausible biological assumptions? The objective of this paper is to answer this question.

References

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M.A. Bedau, Can Unrealistic Computer Models Illuminate Theoretical Biology?, GECCO1999 -- Proceedings of the 1999 Genetic and Evolutionary Computation Conference Workshop Program, 1999
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D.L. DeAngelis and W.M. Mooij, Individual-Based Modeling of Ecological and Evolutionary Processes, Annual Reviews in Ecology, Evolution and Systematics, 2005
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C. Di Chio, R. Poli and P. Di Chio, Extending the Particle Swarm Algorithm to Model Animal Foraging Behaviour, University of Essex, Technical Report, 2006.
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C. Di Chio, R. Poli and P. Di Chio, Modelling Group-Foraging Behaviour with Particle Swarms, PPSN2006 -- Ninth International Conference on Parallel Problem Solving from Nature, 2006.
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E.A. Di Paolo, J. Noble and S. Bullock, Simulation Models as Opaque Thought Experiments, Artificial Life VII -- Proceedings of the Seventh International Conference on the Simulation and Synthesis of Living Systems, 2000.
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J. Kennedy and R.C. Eberhart, Swarm Intelligence, Morgan Kaufmann Publishers, 2001.
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J. Krause and G.D. Ruxton, Living in Groups, Oxford University Press, 2002.
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D. MacFarland, Animal behaviour, Longman, 1999.
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J.K. Parrish and W.M. Hamner, Animal Groups in Three Dimensions, Cambridge University Press, 1997.
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J.W. Pitchford, A. James and J. Brindley, Optimal Foraging in Patchy Turbulent Environments, Marine Ecology Progress Series, 2003

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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2007

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Author Tags

  1. adaptive behaviour
  2. artificial life
  3. biological application
  4. particle swarm
  5. swarm intelligence

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GECCO07
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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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