Reinforcement learning in spatial public goods games with environmental feedbacks

Shaojie Lv, Jiaying Li and Changheng Zhao

Chaos, Solitons & Fractals, 2025, vol. 195, issue C

Abstract: The feedback between strategy and environment is ubiquitous in nature and human society, which has been receiving increasing attention from researchers. Meanwhile, Q-learning allows players to explore the optimal strategy by interacting with the environment. In this paper, we introduce the Q-learning into the spatial public goods game with environmental feedbacks. The simulation results show that the environmental feedback can promote cooperation. The increase of synergy coefficient r and strength of the environmental feedback α is beneficial for the evolution of cooperation. The effects of discount factor γ on the cooperation level of the population are non-monotonic. When r or α is low, the high values of γ can promote the emergence of cooperation. However, with the increase of r and α, the low values of γ are more favorable to the evolution of cooperation.

Keywords: Evolutionary game; Environmental feedback; Reinforcement learning; Cooperation (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077925003091
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:195:y:2025:i:c:s0960077925003091

DOI: 10.1016/j.chaos.2025.116296

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().