Gamification of the optimization problem and multi-point type optimization methods

Takashi Okamoto, Eitaro Aiyoshi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this study, we transform an optimization problem into a game problem by multiple decision makers. This transformation is called gamification of the optimization problem. Then, we discuss correspondence of the dynamics to search the rational solution of the game problem with the multi-point type optimization method to search the optimal solution of the original problem. Specifically, we propose a condition to compose objective functions of multiple decision makers who interfere with each other from the objective function of the original problem so that equivalence of the Nash equilibrium solution of the game problem to the optimal solution of the original problem is guaranteed. Then, correspondence of the gradient dynamics to solve the game problem with the multi-point type optimization method is discussed. We also show some numerical examples in order to explain the gamification of the optimization problem.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Pages3516-3522
Number of pages7
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 - Manchester, United Kingdom
Duration: 2013 Oct 132013 Oct 16

Publication series

NameProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013

Other

Other2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
CountryUnited Kingdom
CityManchester
Period13/10/1313/10/16

Keywords

  • Game problem
  • Multi-point type optimization method
  • Nash equilibrium solution
  • Optimization

ASJC Scopus subject areas

  • Human-Computer Interaction

Cite this

Okamoto, T., & Aiyoshi, E. (2013). Gamification of the optimization problem and multi-point type optimization methods. In Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 (pp. 3516-3522). [6722353] (Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013). https://doi.org/10.1109/SMC.2013.600