Conspecific emotional cooperation biases population dynamics:a cellular automata approach

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Item Type:	Article
Title:	Conspecific emotional cooperation biases population dynamics:a cellular automata approach
Creators Name:	Olsen, M.M., Harrington, K.I. and Siegelmann, H.T.
Abstract:	In this paper, the authors evaluate the benefit of emotions in population dynamics and evolution. The authorsenhance a 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.In this paper, the authors evaluate the benefit of emotions in population dynamics and evolution. The authorsenhance a 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.
Keywords:	Artificial Life, Cellular Automata, Emotion, Population Dynamics, Predator-Prey, Animals, Foxes, Rabbits
Source:	International Journal of Natural Computing Research
Title of Book:	Nature-Inspired Computing Design, Development, and Applications
ISSN:	1947-928X
Publisher:	IGI Global
Volume:	1
Number:	3
Page Range:	51-65
Date:	July 2010
Official Publication:	https://doi.org/10.4018/jncr.2010070104

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