Julio Añasco, Bryan Josué Naranjo Navas, Pamela Anahí Proaño Mora, Maria Anastasia Vasileuski Kramskova
{"title":"Simulation of ultimatum game with artificial intelligence and biases","authors":"Julio Añasco, Bryan Josué Naranjo Navas, Pamela Anahí Proaño Mora, Maria Anastasia Vasileuski Kramskova","doi":"10.18272/aci.v15i1.2304","DOIUrl":null,"url":null,"abstract":"In this research we have developed experimental designs of the ultimatum game with supervised agents. This agents have unbiased and biased thinking depending on the case. We used Reinforcement Learning and Bucket Brigade to program the artficial agentes. We used simulations and behavior comparison to answer the following questions: Does artificial intelligence reach a perfect subgame equilibrium in the ultimatum game experiment? How would Artificial Intelligence behave in the Ultimatum Game experiment if biased thinking is included in it? This exploratory analysis showed one important result: artificial inteligence by itself doesn´t reach a perfect subgame equilibrium. Whereas, the experimental designs with biased thinking agents quickly converge to an equilibrium. Finally, we demonstrated that the agents with envy bias behaves the same as the ones with altruistic bias.","PeriodicalId":42541,"journal":{"name":"Avances en Ciencias e Ingenieria","volume":"224 1","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Avances en Ciencias e Ingenieria","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18272/aci.v15i1.2304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this research we have developed experimental designs of the ultimatum game with supervised agents. This agents have unbiased and biased thinking depending on the case. We used Reinforcement Learning and Bucket Brigade to program the artficial agentes. We used simulations and behavior comparison to answer the following questions: Does artificial intelligence reach a perfect subgame equilibrium in the ultimatum game experiment? How would Artificial Intelligence behave in the Ultimatum Game experiment if biased thinking is included in it? This exploratory analysis showed one important result: artificial inteligence by itself doesn´t reach a perfect subgame equilibrium. Whereas, the experimental designs with biased thinking agents quickly converge to an equilibrium. Finally, we demonstrated that the agents with envy bias behaves the same as the ones with altruistic bias.