Abstract
We consider a version of the ultimatum game which simultaneously combines reactive and Darwinian aspects with offers in [0,1]. By reactive aspects, we consider the effects that lead the player to change their offer given the previous result. On the other hand, Darwinian aspects correspond to copying a better strategy according to best game payoff when the current player compares with one of their neighbours. Therefore, we consider three different strategies, which govern how the players change their offers: greedy, moderate, and conservative. First, we provide an analytic study of a static version of game, where Darwinian aspects are not considered. Then, by using numerical simulations of a detailed and complete multi-agent system on a two dimensional lattice, we add an extra feature, in which players probabilistically escape from extreme offers (those close to 0 or 1) for obvious reasons. The players are also endowed reciprocity on their gains as proposers, which is reflected on their gains as responders. We also analyse the influence of the player's mobility effects. An analysis of the emergence of coexistence of strategies and changes on the dominant strategies are observed, which in turn depends on the player's mobility rate.
Original language | English |
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Article number | 104956 |
Journal | Communications in Nonlinear Science and Numerical Simulation |
Volume | 80 |
DOIs | |
State | Published - Jan 2020 |
Bibliographical note
Publisher Copyright:© 2019 Elsevier B.V.
Funding
Roberto da Silva thanks CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico for financial support under grant numbers: 311236/2018-9 , and 424052/2018-0 . Luis Lamb is partly supported by CNPq and by CAPES - Coordenação de Aperfeiç oamento de Pessoal de Nível Superior - Financed Code 001 . This work was partly developed using the computational resources of Cluster Ada, IF-UFRGS. Roberto da Silva thanks CNPq - Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico for financial support under grant numbers: 311236/2018-9, and 424052/2018-0. Luis Lamb is partly supported by CNPq and by CAPES - Coordena??o de Aperfei? oamento de Pessoal de N?vel Superior - Financed Code 001. This work was partly developed using the computational resources of Cluster Ada, IF-UFRGS.
Funders | Funder number |
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Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico | |
Coordenação de Aperfeiç oamento de Pessoal de Nível Superior | |
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior | |
Conselho Nacional de Desenvolvimento Científico e Tecnológico | 424052/2018-0, 311236/2018-9 |
Keywords
- Analytical methods
- Evolutionary ultimatum game
- Multi-agent systems
- Numerical simulations