2015/01/26 by Heinrich H. Nax, Matjaz Perc, Matjaž Perc · 69 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · Physics and Astronomy · Social Sciences · #Artificial intelligence #Best response #Computer science #Economics #Evolutionary Game Theory and Cooperation #Experimental Behavioral Economics Studies #Game Theory and Applications #Game theory #Mathematical economics #Microeconomics #Nash equilibrium #Population #Provisioning #Public good #Public goods game #Reinforcement learning #Repeated game #Social learning #cs.GT #physics.soc-ph #q-bio.PE
paper · pdf · doi:10.1038/srep08010
published in Scientific Reports 5(1), 8010 (Nature Portfolio) · 7 two-column pages, 3 figures; accepted for publication in Scientific Reports
arxiv created 2015/01/26 · openalex publication_date 2015/01/26 · arxiv updated 2015/01/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We consider an environment where players are involved in a public goods game and must decide repeatedly whether to make an individual contribution or not. However, players lack strategically relevant information about the game and about the other players in the population. The resulting behavior of players is completely uncoupled from such information, and the individual strategy adjustment dynamics are driven only by reinforcement feedbacks from each player's own past. We show that the resulting "directional learning" is sufficient to explain cooperative deviations away from the Nash equilibrium. We introduce the concept of k-strong equilibria, which nest both the Nash equilibrium and the Aumann-strong equilibrium as two special cases, and we show that, together with the parameters of the learning model, the maximal k-strength of equilibrium determines the stationary distribution. The provisioning of public goods can be secured even under adverse conditions, as long as players are sufficiently responsive to the changes in their own payoffs and adjust their actions accordingly. Substantial levels of public cooperation can thus be explained without arguments involving selflessness or social preferences, solely on the basis of uncoordinated directional (mis)learning.