Games with Payments between Learning Agents

TL;DR

This paper investigates how monetary payments between autonomous learning agents in repeated games influence learning dynamics, strategic behavior, and welfare, revealing that such payments often lead to collusion and welfare improvements but pose challenges for mechanism design.

Contribution

It introduces a game-theoretic model analyzing incentives for payments among learning agents and demonstrates their impact on outcomes and welfare in various game settings.

Findings

Payments are beneficial for self-interested agents and are not easily avoided.

Endogenous payments can increase overall welfare in many game scenarios.

In auctions, payments lead to collusive outcomes with low revenue for the seller.

Abstract

In repeated games, such as auctions, players rely on autonomous learning agents to choose their actions. We study settings in which players have their agents make monetary transfers to other agents during play at their own expense, in order to influence learning dynamics in their favor. Our goal is to understand when players have incentives to use such payments, how payments between agents affect learning outcomes, and what the resulting implications are for welfare and its distribution. We propose a simple game-theoretic model to capture the incentive structure of such scenarios. We find that, quite generally, abstaining from payments is not robust to strategic deviations by users of learning agents: self-interested players benefit from having their agents make payments to other learners. In a broad class of games, such endogenous payments between learning agents lead to higher welfare for all players. In first- and second-price auctions, equilibria of the induced "payment-policy game" lead to highly collusive learning outcomes, with low or vanishing revenue for the auctioneer. These results highlight a fundamental challenge for mechanism design, as well as for regulatory policies, in environments where learning agents may interact in the digital ecosystem beyond a mechanism's boundaries.