Lim, Ik Soo ORCID: https://orcid.org/0000-0002-9499-8515 and Masuda, Naoki (2023) To trust or not to trust: evolutionary dynamics of an asymmetric N-player trust game. IEEE Transactions on Evolutionary Computation. pp. 1-15. ISSN 1089-778X (Print), 1941-0026 (Online) (doi:10.1109/TEVC.2023.3244537)

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Abstract

Trusting others and reciprocating the received trust with trustworthy actions are fundaments of economic and social interactions. The trust game (TG) is widely used for studying trust and trustworthiness and entails a sequential interaction between two players, an investor and a trustee. It requires at least two strategies or options for an investor (e.g.to trust versus not to trust a trustee). According to the evolutionary game theory, the antisocial strategies (e.g.not to trust) evolve such that the investor and trustee end up with lower payoffs than those that they would get with the prosocial strategies (e.g.to trust). A generalisation of the TG to a multiplayer (i.e.more than two players) TG was recently proposed. However, its outcomes hinge upon two assumptions that various real situations may substantially deviate from: (i) investors are forced to trust trustees and (ii) investors can turn into trustees by imitation and vice versa. We propose an asymmetric multiplayer TG that allows investors not to trust and prohibits the imitation between players of different roles; instead, investors learn from other investors and the same for trustees. We show that the evolutionary game dynamics of the proposed TG qualitatively depends on the nonlinearity of the payoff function and the amount of incentives collected from and distributed to players through an institution. We also show that incentives given to trustees can be useful and sufficient to cost-effectively promote trust and trustworthiness among self-interested players.

Item Type:	Article
Uncontrolled Keywords:	evolutionary game theory; evolutionary dynamics; replicator dynamics; trust game; incentives
Subjects:	B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Related URLs:	https://cis.ieee.org/publications/t-evol...
Last Modified:	24 Feb 2023 10:37
URI:	http://gala.gre.ac.uk/id/eprint/38554

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