Emergent coordination in temporal partitioning congestion games
Year: 2024
Type: article
Abstract: Can a community self-organize to solve a congestion dilemma? In the present article, we study the social dynamic of a distinctive category of congestion games: temporal partitioning games (TPGs), in which participants must coordinate an optimal time-partitioning for using a limited resource. We explore the social dynamic of TPGs with little or no external coordination. Despite a long history of congestion research, the problem of the dynamics of TPGs did not receive much attention. The dilemma underlying TPGs is whether users can self-organize to optimally partition their usage patterns. Reaching an optimal solution may be hindered, however, by a collectively destructive meta-reasoning pattern, trapping users in a socially vicious oscillatory behaviour. We developed a model capturing the dynamics of these games (the ‘black Iris blossom game’) and ran simulations to assess its behavior, based on a 2x2 framework that distinguishes between the players’ knowledge of other players’ choices and whether they use a learning mechanism. We found that when players do not use learning, the game does not converge and an oscillatory dynamic develops, irrespective of the information players possess. Adding learning led to weak convergence in the no-information condition and strong convergence in the with-information condition. The provision of information led to a more robust equilibrium but at the cost of social separation in using the common pool (some fraction of the population enjoys the resource while the rest never does). Although the non-learning models failed to achieve equilibrium, they have one advantage: they made possible a fairer utility distribution because players could use the resource and had positive utility for several seasons, until an overflow occurred, leading to some of the players forgoing the next season, when new players used the opportunity. We also corroborated the validity of our model using real data from a study of bats’ behaviour in an environment of water scarcity. We conclude by examining the merits of a complexity-based, agent-based modelling approach over a game-theoretic one, contending that it offers superior insights into the temporal dynamics of TPGs. We also briefly discuss the policy implications of our findings.
Source: PLoS ONE
Authors: Reuven Cohen, Oren Perez
Institution: Bar-Ilan University
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,290
OpenAlex ID: W4401699226