Safe Havens for Cooperation: An Application of Game Theory
When thinking on the way in which early civilizations are formed, two major questions comes to mind: what incentive was there for cooperation, and what made it work so well?
In a recent research study, they focused on exactly that – how well-functioning networks are formed, especially when individuals in the same network are competing against free-loaders that take advantage of their time and effort. The researchers used game theory to investigate this issue in the context of the “snowdrift game,” a situation in which two drivers are said to be stuck in the snow during a sudden snowstorm and, with each driver having access to a snow shovel, can choose to cooperate or not. Like with any game in game theory, there is a most optimal payoff. In this game, the highest payoff is when one driver becomes a free-loader, allowing the other driver to do all the work of clearing off the snow so that they can return home without doing much to help.
In researching how high levels of cooperation can be attained in a network, the researchers decided to add on a new option to the game. The players were able to quit the scene and relocate to another, meaning that the exploited contributors in the game could leave to a better situation while the free-loaders would then have to face the punishment of figuring out things on their own. This was an interesting situation in the context of game theory, as the research shows that if the contributors quit the scene too fast, both the contributor and the free-loader would end up constantly leaving scenes in search of a better one. In other words, each scenario in the game kept constantly changing to the point each scenario became the same and no cooperation could be reached.
However, it was discovered that there was a transition period in the game where cooperation for a common good was able to be reached. In this transition period, people in the game were more open to the environment and gave it some more time before making a full, conclusive decision to leave the environment once it got too bad. This longer deciding period allows enough contributors to leave the scene for the free-loaders to feel negative effects while also not having each scene become the same situation like before. In other words, there is a “safe haven” for cooperation where the common goals of the game can be reached and each person is able to thrive.
This is an interesting application of game theory as it demonstrates just how dependent a person’s actions are on the other person, especially in the context of a cooperation game. In particular, it shows how the highest payoff in the “snowdrift game” could not be shared among the two individuals as one would ultimately have to either contribute or free-load for that situation to be reached. The added on ability to switch scenes allowed these contributors to leave the situation to reach their highest payoff for their efforts, but what ultimately led to cooperation rather than stagnation was a transition state. In this state in between continually changing situations or just allowing the freeloaders to go without consequences, the freeloaders would be given a chance first. In this way, it shows how games in game theory can also have sharp transition states that can dictate very different outcomes, rather than being one smooth transition to a final result.
Sources:
University of Oldenburg. “Safe havens for cooperation: Using game theory to find out how networks with a high level of cooperation form.” ScienceDaily. Science Daily, 11 August 2022.