Ryohei Matsumoto, Momoko Kanmura, K. Ohnishi, Shinya Watanabe
{"title":"Evolutionary Problem Solving by People Being Aware of Others’ Preferences","authors":"Ryohei Matsumoto, Momoko Kanmura, K. Ohnishi, Shinya Watanabe","doi":"10.1109/ICAWST.2018.8517250","DOIUrl":null,"url":null,"abstract":"-Interactive and human-based evolutionary computation methods both enable people to solve a given problem together, but it is hard for us to analyze the processes of the problem solving because people interact with each other nonlinearly in the methods. Therefore, studies of those evolutionary methods are likely to be practical. To make such evolutionary methods involving people more widely used, they need to be traceable and obtain more trust from users. So, in this study, we develop a new traceable evolutionary method involving people. In the method, two or more people produce and evaluate solutions in turn one by one, while being aware of the preferences of each other. In addition, assuming two people solve a problem together, we construct not only an experimental system for the method but also asimulation model of the experimental system. Then, we obtain results of experiments by human subjects and simulations and realize from the results that the simulation results assuming completely rational people are different from the experimental ones, in which cooperation beyond rationality among people can occur.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 9th International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAWST.2018.8517250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
-Interactive and human-based evolutionary computation methods both enable people to solve a given problem together, but it is hard for us to analyze the processes of the problem solving because people interact with each other nonlinearly in the methods. Therefore, studies of those evolutionary methods are likely to be practical. To make such evolutionary methods involving people more widely used, they need to be traceable and obtain more trust from users. So, in this study, we develop a new traceable evolutionary method involving people. In the method, two or more people produce and evaluate solutions in turn one by one, while being aware of the preferences of each other. In addition, assuming two people solve a problem together, we construct not only an experimental system for the method but also asimulation model of the experimental system. Then, we obtain results of experiments by human subjects and simulations and realize from the results that the simulation results assuming completely rational people are different from the experimental ones, in which cooperation beyond rationality among people can occur.