Proc Natl Acad Sci U S A. 2011 Aug 9;108(32):13335-40. doi: 10.1073/pnas.1102131108. Epub 2011 Jul 25.

Evolution of direct reciprocity under uncertainty can explain human generosity in one-shot encounters.

Delton AW, Krasnow MM, Cosmides L, Tooby J.

Source

Center for Evolutionary Psychology, Department of Psychology and Anthropology, University of California, Santa Barbara, CA 93106, USA.

Abstract

Are humans too generous? The discovery that subjects choose to incur costs to allocate benefits to others in anonymous, one-shot economic games has posed an unsolved challenge to models of economic and evolutionary rationality. Using agent-based simulations, we show that such generosity is the necessary byproduct of selection on decision systems for regulating dyadic reciprocity under conditions of uncertainty. In deciding whether to engage in dyadic reciprocity, these systems must balance (i) the costs of mistaking a one-shot interaction for a repeated interaction (hence, risking a single chance of being exploited) with (ii) the far greater costs of mistaking a repeated interaction for a one-shot interaction (thereby precluding benefits from multiple future cooperative interactions). This asymmetry builds organisms naturally selected to cooperate even when exposed to cues that they are in one-shot interactions.

Comment in

Flexible strategies, forgiveness, and the evolution of generosity in one-shot encounters. [Proc Natl Acad Sci U S A. 2011]
Flexible strategies, forgiveness, and the evolution of generosity in one-shot encounters.McNally L, Tanner CJ. Proc Natl Acad Sci U S A. 2011 Nov 1; 108(44):E971; author reply E972. Epub 2011 Oct 25.

PMID:: 21788489; [PubMed - indexed for MEDLINE]
PMCID:: PMC3156224

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Fig. 3.

One-shot cooperation evolves when interactions are moderately long and benefits are moderately large. (A) Example evolutionary dynamics showing that the probability of cooperation, given a rational (ideal Bayesian) belief that an interaction is one-shot, evolves to be high when the motivational architecture is allowed to evolve based on its fitness consequences. (B) Aggregated final stabilized values across all runs where the motivational architecture is free to evolve and half of all interactions are repeated; this example shows that the probability of cooperating despite a rational belief that an interaction is one-shot evolves to be high except when the benefits of cooperating and the average length of repeated interactions are both small. (C) Example evolutionary dynamics showing that agents evolve to become highly resistant to concluding that interactions are one-shot, even in the face of strong evidence that interactions are one-shot, when the weight of evidence required by the cognitive architecture is allowed to evolve. These stringent thresholds to conclude the interaction is one-shot results in a high probability of cooperating, even when the interaction is actually one-shot. (D) Aggregated final stabilized values across all runs where the cognitive architecture is free to evolve and one half of all interactions are repeated. These data show that the probability of cooperating when the interaction is one-shot evolves to be high, except when benefits of cooperating and the average length of repeated interaction are both small. For A and C, the benefit to cost ratio is 3:1, half of all interactions are repeated, and the distance between cue summary distributions (a measure of the ease of discriminating one-shot from repeated interactions) is 2 SDs. Traditionally, it has been assumed that the highest paying strategy is to cooperate 0% of the time whenever an interaction is likely to be one-shot.

Evolution of direct reciprocity under uncertainty can explain human generosity in one-shot encounters

Proc Natl Acad Sci U S A. 2011 August 9;108(32):13335-13340.