Why individuals engage in costly behaviors that benefit others has long been an important question in evolutionary biology. Most of the theory trying to resolve this “dilemma of cooperation” focused on kin selection or notions of reciprocity. Here, we present a new theoretical approach to the evolution of cooperative behavior. Our approach is two-tiered: we first model the behavioral dynamics of an interaction between two unrelated individuals, and then ask how evolution affects the behavioral dynamics. The behavioral dynamics are driven by the internal motivations of the individuals, which are evolved traits of individuals. We present a general mathematical framework to model the evolution of motivations and apply this framework to a game representing the dilemma of cooperation.

Results/Conclusions

The evolutionary stable motivations in this game are such that individuals “care” for each other's payoff as well as their own. In other words, purely selfish motivations that lead to maximization of individual payoff may not be evolutionary stable. The evolution of mutual regard causes individuals to invest into helping each other, and results in a mutually beneficial interaction. We also consider the possible consequences of disagreement (i.e. behavioral conflict) between individuals, and find that if disagreement is costly, the evolutionary stable level of mutual regard increases. In the limit as disagreement becomes more costly, the evolutionary stable behavioral dynamics converge to the Nash Bargaining Solution that maximizes the product of the two individuals' payoffs. Our two-tiered framework that incorporates autonomous behavioral dynamics opens up interesting venues for behavioral evolution.