A prey–predator model of learning based on bit string with intelligence

Mingfeng He, Qiuhui Pan and Zhirui Wang

Physica A: Statistical Mechanics and its Applications, 2007, vol. 377, issue 1, 131-137

Abstract: A prey–predator model of learning based on bit string with intelligence is developed in this paper. Three bit strings are taken into account which describe the health, the intelligence and the knowledge, respectively. A prey–predator ecosystem is simulated on lattices based on Monte-Carlo method. Then, we present the results of our simulations and discuss the evolution of population, intelligence and knowledge, respectively. From the results we find that for coexistence of predator and prey, higher average knowledge of the predator automatically leads to higher average intelligence of the prey. It can be concluded that each species has some advantage, thus they can coexist in an ecosystem for ever.

Keywords: Penna model; Prey–predator; Intelligence (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:377:y:2007:i:1:p:131-137

DOI: 10.1016/j.physa.2006.11.041

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