Cooperation, Retaliation and Forgiveness in Revision Games
Dong Hao, Qi Shi, Jinyan Su, Bo An

TL;DR
This paper introduces Limited Retaliation strategies in revision games, which promote cooperation, deter betrayal, and allow forgiveness, offering a robust, welfare-optimizing, and computationally efficient approach for multi-agent interactions.
Contribution
It proposes a novel class of strategies called Limited Retaliation, improving upon Grim Trigger by balancing cooperation, retaliation, and forgiveness in revision games.
Findings
Limited Retaliation strategies are cooperative and vengeful.
They outperform Grim Trigger in stability and social welfare.
Strategies are simple to derive and computationally efficient.
Abstract
Revision game is a very new model formulating the real-time situation where players dynamically prepare and revise their actions in advance before a deadline when payoffs are realized. It is at the cutting edge of dynamic game theory and can be applied in many real-world scenarios, such as eBay auction, stock market, election, online games, crowdsourcing, etc. In this work, we novelly identify a class of strategies for revision games which are called Limited Retaliation strategies. An limited retaliation strategy stipulates that, (1) players first follow a recommended cooperative plan; (2) if anyone deviates from the plan, the limited retaliation player retaliates by using the defection action for a limited duration; (3) after the retaliation, the limited retaliation player returns to the cooperative plan. A limited retaliation strategy has three key features. It is cooperative,…
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Taxonomy
TopicsGame Theory and Applications · Auction Theory and Applications · Experimental Behavioral Economics Studies
