Abstract
SummaryGlobal coordination is required to solve a wide variety of challenging collective action problems from network colorings to the tragedy of the commons. Recent empirical study shows that the presence of a few noisy autonomous agents can greatly improve collective performance of humans in solving networked color coordination games. To provide analytical insights into the role of behavioral randomness, here we study myopic artificial agents attempting to solve similar network coloring problems using decision update rules that are only based on local information but allow random choices at various stages of their heuristic reasonings. We show that the resulting efficacy of resolving color conflicts is dependent on the implementation of random behavior of agents and specific population characteristics. Our work demonstrates that distributed greedy optimization algorithms exploiting local information should be deployed in combination with occasional exploration via random choices in order to overcome local minima and achieve global coordination.
Highlights
Many classical games like the Prisoner’s Dilemma focus on two players attempting to get the better of each other
Recent empirical study shows that the presence of a few noisy autonomous agents can greatly improve collective performance of humans in solving networked color coordination games
To provide analytical insights into the role of behavioral randomness, here we study myopic artificial agents attempting to solve similar network coloring problems using decision update rules that are only based on local information but allow random choices at various stages of their heuristic reasonings
Summary
Many classical games like the Prisoner’s Dilemma focus on two players attempting to get the better of each other. A great body of work is focused on how to foster cooperation in such nonzero sum games (Nowak, 2006b; Doebeli and Hauert 2005). There is another well-studied class of games in which all players receive the most benefit when they work together, called coordination games (Skyrms 2004). The optimal behavior for all players can be determined and agreed upon if all players can meet and strategize beforehand In such games, the difficulty comes not from attempting to scam one’s opponent but figuring out what one’s partner will play before choosing one’s own strategy (Huyck et al, 1990; Nowak 2006a). There can still be a ‘‘defecting’’ component, in which one’s opponent can unilaterally choose a strategy with lower maximum payoff and less risk (Fang et al, 2002)
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