The Evolution of Lying in a Spatially-Explicit Prisoner's Dilemma Model

TL;DR

This paper introduces a spatial prisoner's dilemma model where individuals can lie about their last move, showing how populations evolve towards honesty or dishonesty based on their strategies and payoffs.

Contribution

It presents a novel spatial model incorporating evolving truth-telling probabilities, revealing stable populations of liars or truth-tellers in a prisoner's dilemma context.

Findings

Populations of high truth-tellers tend to evolve from mixed populations.

Lying populations are stable when their average scores surpass those of honest groups.

The model applies to both human and animal social behaviors.

Abstract

I present the results from a spatial model of the prisoner's dilemma, played on a toroidal lattice. Each individual has a default strategy of either cooperating ($C$) or defecting ($D$). Two strategies were tested, including ``tit-for-tat'' (TFT), in which individuals play their opponent's last play, or simply playing their default play. Each individual also has a probability of telling the truth ($0 \leq P_{truth} \leq 1$) about their last play. This parameter, which can evolve over time, allows individuals to be, for instance, a defector but present as a cooperator regarding their last play. This leads to interesting dynamics where mixed populations of defectors and cooperators with $P_{truth} \geq 0.75$ move toward populations of truth-telling cooperators. Likewise, mixed populations with $P_{truth} < 0.7$ become populations of lying defectors. Both such populations are stable because they each have higher average scores than populations with intermediate values of $P_{truth}$. Applications of this model are discussed with regards to both humans and animals.