Particle Swarm Optimization Algorithm for Agent-Based Artificial Markets |
| |
Authors: | Tong Zhang B Wade Brorsen |
| |
Affiliation: | 1.Research Institute of Economics and Management,Southwestern University of Finance and Economics,Chengdu,People’s Republic of China;2.Department of Agricultural Economics,Oklahoma State University,Stillwater,USA |
| |
Abstract: | Particle swarm optimization (PSO) is adapted to simulate dynamic economic games. The robustness and speed of the PSO algorithm
is compared to a genetic algorithm (GA) in a Cournot oligopsony market. Artificial agents with the PSO learning algorithm
find the optimal strategies that are predicted by theory. PSO is simpler and more robust to changes in algorithm parameters
than GA. PSO also converges faster and gives more precise answers than the GA method which was used by some previous economic
studies. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |