Abstract
We are investigating an attraction mechanism that models interpersonal relations such that an individual acts differently, and presumably more cooperatively, with those to whom it is attracted than with others. This is a generic mechanism and the types of relations envisaged can range from regular physical attraction to attachment of toddlers to caregivers. We have shown in the past that the introduction of this attraction mechanism in an iterated prisoner’s dilemma game yields higher average agent scores in tournaments within uniform or mixed populations. In the present work, we show that this mechanism has an evolutionary advantage and that it can evolve in various ways (probability of attraction, network of attraction). These results show that cooperation and social stability can be enhanced by psychological mechanisms that are external to the game setting but interfere with it and that these mechanisms may be further selected and reinforced by evolution and catalyze cooperation. We further show that evolution of attraction in the context of cooperation is possible in fairly small networks of homogeneous agents with noise but not in networks of heterogeneous agents without noise. This remark has interesting implications for the study of the origins of human cognition.
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Notes
- 1.
Note that the standard deviations for M, avg. K and avg. Score at generation 100 are 2.66, 1.183 and 210.672, respectively. The averages at generation 100 are therefore many standard deviations away from the averages at generation 0, therefore the results are significant in the long term, despite the very common occasional fluctuations inherent in all evolutionary systems.
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Tzafestas, E. (2024). Evolution of Attraction for Cooperation. In: Villani, M., Cagnoni, S., Serra, R. (eds) Artificial Life and Evolutionary Computation. WIVACE 2023. Communications in Computer and Information Science, vol 1977. Springer, Cham. https://doi.org/10.1007/978-3-031-57430-6_30
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