Teaching and learning in a probabilistic prisoner's dilemma

The prisoner's dilemma is much studied in social psychology and decision-making because it models many real-world conflicts. In everyday terms, the choice to 'cooperate' (maximize reward for the group) or 'defect' (maximize reward for the individual) is often attributed to altruistic or selfish motives. Alternatively, behavior during a dilemma may be understood as a function of reinforcement and punishment. Human participants played a prisoner's-dilemma-type game (for points exchangeable for money) with a computer that employed either a teaching strategy (a probabilistic version of tit-for-tat), in which the computer reinforced or punished participants' cooperation or defection, or a learning strategy (a probabilistic version of Pavlov), in which the computer's responses were reinforced and punished by participants' cooperation and defection. Participants learned to cooperate against both computer strategies. However, in a second experiment which varied the context of the game, they learned to cooperate only against one or other strategy; participants did not learn to cooperate against tit-for-tat when they believed that they were playing against another person; participants did not learn to cooperate against Pavlov when the computer's cooperation probability was signaled by a spinner. The results are consistent with the notion that people are biased not only to cooperate or defect on individual social choices, but also to employ one or other strategy of interaction in a pattern across social choices.