Abstract
In principle, any cooperative behaviour can be evolutionarily stable as long as it is incentivized by a reward from the beneficiary, a mechanism that has been called reciprocal cooperation. However, what makes this mechanism so powerful also has an evolutionary downside. Reciprocal cooperation faces a chicken-and-egg problem of the same kind as communication: it requires two functions to evolve at the same time—cooperation and response to cooperation. As a result, it can only emerge if one side first evolves for another reason, and is then recycled into a reciprocal function. Developing an evolutionary model in which we make use of machine learning techniques, we show that this occurs if the fact to cooperate and reward others’ cooperation become general abilities that extend beyond the set of contexts for which they have initially been selected. Drawing on an evolutionary analogy with the concept of generalization, we identify the conditions necessary for this to happen. This allows us to understand the peculiar distribution of reciprocal cooperation in the wild, virtually absent in most species—or limited to situations where individuals have partially overlapping interests, but pervasive in the human species.