Different Kinds of Cooperative Strategies among Humans Develop

Cooperation is critical in evolution. A group of scientists has now developed a new model that demonstrates how various types of cooperative strategies among humans develop. They demonstrate, using a unified framework, how an individual’s experience and the reputation of others influence the emergence of successful cooperation.

Cooperation has evolved as a successful strategy in both nature and human society, but comprehending its emergence can be difficult. To create a model that can be used for predictions and simulations, researchers must abstract interactions between individuals into mathematical formulas. The emergence of cooperation among selfish agents with no incentive to cooperate is a complex phenomenon that has long piqued the interest of biologists, social scientists, and physicists.

They frequently investigate the strategies of players in a simple game of giving and receiving benefits in the field of evolutionary game theory. Such strategies instruct players on how to act in a given interaction. The findings of the scientists contradict the popular belief that only the strongest and most selfish flourish and survive. Instead, they demonstrate how collaboration can be a successful and long-term strategy.

A team of scientists created a new model that shows how different kinds of cooperative strategies among humans develop. They have to abstract interactions between individuals into mathematical formulas to be able to create a model that can be used for predictions and simulations.

Researchers from the Chatterjee group at IST Austria, led by Laura Schmid, have developed a new mathematical framework that combines previously incompatible descriptions of cooperation. They demonstrate how prior experiences with and the reputation of a potential partner affect a player’s willingness to cooperate with them in their simulations of many interactions between players.

Scratched Backs and Flawless Reputation

The researchers’ work revolves around interactions based on direct and indirect reciprocity. “An interaction based on direct reciprocity simply means ‘I’ll scratch your back if you scratch mine,'” Laura Schmid explains.

Indirect reciprocity, on the other hand, is based on an individual’s reputation. “This means that if they treat others well, I will cooperate with them even if I have never interacted with that individual before,” Schmid continues, “but this has so far only been demonstrated conclusively among humans.”

The emergence of cooperation

It is not easy to resolve conflicts that arise when these two types of reciprocity lead to competing suggestions. Should the player work with someone who treats others well, even if they have treated them unfairly in the past? The strategies employed by the players then provide an answer to this type of question.

One of the key findings from the researchers’ unified model of both direct and indirect reciprocity was that the evolution of strategies, the amount of cooperation, and the type of reciprocity individuals prefer all depend on the environment: factors such as how frequently players interact and whether they know the truth about their partner’s reputation.

Stabilized Cooperation

This model can aid researchers in understanding the fundamental dynamics of cooperative strategy evolution and stabilization. “We investigated which strategies of direct or indirect reciprocity give rise to a Nash equilibrium using mathematical tools that were developed only recently,” Schmid explains. “Once our simulation’s evolving population of players adopts such strategies, none of them has an incentive to divert.”

These findings shed some light on how social norms based on experience and reputation may have influenced the evolution of cooperation in early human societies. A more recent application would be the modeling of online store rating systems based on both a buyer’s personal experience and a seller’s reputation.

Laura Schmid has been interested in bridging different fields, such as game theory and evolutionary modeling, for some time. Growing up in Vienna, she first studied physics at TU Wien and piano at the Music and Arts University of the City of Vienna before pursuing her Ph.D. with the Chatterjee group at IST Austria. She intends to continue her research career abroad after finishing her degree later this year.

Laura Schmid plans to investigate how many players in a group must use an indirect reciprocity strategy for it to be successful in the future. She will be able to investigate the impact of the spread of social norms within society using this method.