Conspecific Emotional Cooperation Biases Population Dynamics: A Cellular Automata Approach

Megan M. Olsen, Kyle I. Harrington and Hava T. Siegelmann
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Megan M. Olsen: University of Massachusetts Amherst, USA
Kyle I. Harrington: Brandeis University, USA
Hava T. Siegelmann: University of Massachusetts Amherst, USA

International Journal of Natural Computing Research (IJNCR), 2010, vol. 1, issue 3, 51-65

Abstract: In this paper, the authors evaluate the benefit of emotions in population dynamics and evolution. The authors enhance cellular automata (CA) simulating the interactions of competing populations with emotionally inspired rules in communication, interpretation, and action. While CAs have been investigated in studies of population dynamics due to their ability to capture spatial interactions, emotion-like interactions have yet to be considered. Our cellular stochastic system describes interacting foxes that feed on rabbits that feed on carrots. Emotions enable foxes and rabbits to improve their decisions and share their experiences with neighboring conspecifics. To improve the system’s biological relevance, it includes inter-species disease transmission, and emotions encode data pertaining to both survival and epidemic reduction. Results indicate that emotions increase adaptability, help control disease, and improve survival for the species that utilizes them. Simulations support the hypothesis that the acquisition of emotion may be an evolutionary result of competitive species interactions.

Date: 2010
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