Effect of expanding learning scope on the evolution of cooperation in scale-free networks
Masaaki Inaba, Eizo Akiyama

TL;DR
This paper investigates how expanding the scope for selecting game and learning partners influences cooperation in public goods games on scale-free networks, revealing complex effects on cooperation rates.
Contribution
It uncovers novel mechanisms by which partner selection scope impacts cooperation, including suppression and promotion effects, in scale-free network settings.
Findings
Expanding game partner scope suppresses cooperation.
Expanding learning partner scope promotes cooperation when difficult.
Further expanding learning scope can recover cooperation rates.
Abstract
We study how expanding the scope for selecting game and learning (adaptation) partners affects the evolution of cooperation in public goods games on scale-free networks. We show the following three results. (i) Expanding the scope for selecting game partners suppresses cooperation. (ii) Expanding the scope for selecting learning partners promotes cooperation when cooperation evolution is difficult. (iii) When cooperation is more likely to evolve, slightly expanding the scope for selecting learning partners causes a significant drop in the cooperation rate, but expanding the scope further causes the cooperation rate to recover. Although (i) is explained by the hub-centered mechanism, the well-known dynamic that promotes cooperation on scale-free networks, (ii) and (iii) are caused by a completely different mechanism that has heretofore been rarely mentioned.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEvolutionary Game Theory and Cooperation · Evolution and Genetic Dynamics · Mathematical and Theoretical Epidemiology and Ecology Models
