Decoding trust: A reinforcement learning perspective

TL;DR

This paper demonstrates that trust and trustworthiness can naturally emerge through reinforcement learning mechanisms, specifically Q-learning, without external factors, offering insights into human social behavior.

Contribution

It introduces a reinforcement learning framework using Q-learning to explain the emergence of trust and trustworthiness in the trust game, challenging previous imitative learning models.

Findings

High trust and trustworthiness emerge when individuals consider both historical experience and future returns.

The evolution of Q-tables shows a crossover resembling human psychological changes.

Results are robust in lattice population extensions.

Abstract

Behavioral experiments on the trust game have shown that trust and trustworthiness are universal among human beings, contradicting the prediction by assuming \emph{Homo economicus} in orthodox Economics. This means some mechanism must be at work that favors their emergence. Most previous explanations however need to resort to some factors based upon imitative learning, a simple version of social learning. Here, we turn to the paradigm of reinforcement learning, where individuals update their strategies by evaluating the long-term return through accumulated experience. Specifically, we investigate the trust game with the Q-learning algorithm, where each participant is associated with two evolving Q-tables that guide one's decision making as trustor and trustee respectively. In the pairwise scenario, we reveal that high levels of trust and trustworthiness emerge when individuals appreciate both their historical experience and returns in the future. Mechanistically, the evolution of the Q-tables shows a crossover that resembles human's psychological changes. We also provide the phase diagram for the game parameters, where the boundary analysis is conducted. These findings are robust when the scenario is extended to a latticed population. Our results thus provide a natural explanation for the emergence of trust and trustworthiness without external factors involved. More importantly, the proposed paradigm shows the potential in deciphering many puzzles in human behaviors.