Name
Abstract | ||
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We introduce the swarm intelligence methods into the evolutionary dynamics.We integrate the best personal strategy in the past with the best current strategy in the neighborhood.The cooperation level is enhanced markedly by the swarm intelligence. In this paper, we introduce the swarm intelligence methods into the evolutionary dynamics, and have studied the impact of swarm intelligent algorithm on the evolution of cooperation among selfish individuals in the continuous version of spatial public goods games (PGG). We update an individuals strategy according to the memory which records the most successful individual strategy in the past (referred to as its personal best strategy) as well as the knowledge of the best current strategy found by its nearest neighbors (referred to as the neighborhood best strategy). Through extensive simulations, we find that the introduction of swarm intelligence into PGG can promote cooperation strongly. Other pertinent quantities such as the time evolution of cooperator density, the spatial distribution of strategies and the updated velocities are also investigated.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.amc.2017.10.022 | Applied Mathematics and Computation |
Keywords | Field | DocType |
02.50.Le, 64.60.ah, 89.75.Hc, Cooperation, Public goods games, Square lattice, Swarm intelligence | Mathematical optimization,Public good,Swarm behaviour,Swarm intelligence,Artificial intelligence,Evolutionary dynamics,Mathematics | Journal |
Volume | ISSN | Citations |
320 | 0096-3003 | 1 |
PageRank | References | Authors |
0.35 | 19 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ya-Shan Chen | 1 | 1 | 0.35 |
| Han-Xin Yang | 2 | 31 | 5.94 |
| Wenzhong Guo | 3 | 611 | 76.01 |
| Genggeng Liu | 4 | 67 | 8.94 |