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 language | English |
|---|---|
| Title of host publication | Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 |
| Pages | 3516-3522 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 - Manchester, United Kingdom Duration: 2013 Oct 13 → 2013 Oct 16 |
Other
| Other | 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 |
|---|---|
| Country | United Kingdom |
| City | Manchester |
| Period | 13/10/13 → 13/10/16 |
Keywords
- Game problem
- Multi-point type optimization method
- Nash equilibrium solution
- Optimization
ASJC Scopus subject areas
- Human-Computer Interaction
Cite this
Gamification of the optimization problem and multi-point type optimization methods. / Okamoto, Takashi; Aiyoshi, Eitaro.
Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013. 2013. p. 3516-3522 6722353.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Gamification of the optimization problem and multi-point type optimization methods
AU - Okamoto, Takashi
AU - Aiyoshi, Eitaro
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Game problem
KW - Multi-point type optimization method
KW - Nash equilibrium solution
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=84893599767&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893599767&partnerID=8YFLogxK
U2 - 10.1109/SMC.2013.600
DO - 10.1109/SMC.2013.600
M3 - Conference contribution
AN - SCOPUS:84893599767
SN - 9780769551548
SP - 3516
EP - 3522
BT - Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
ER -