Smart Contracts for Trustless Sampling of Correlated Equilibria
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 3744-3752.
https://doi.org/10.24963/ijcai.2025/416
Keywords
- Game Theory and Economic Paradigms: GTEP: Mechanism design
- Game Theory and Economic Paradigms: GTEP: Noncooperative games
- Game Theory and Economic Paradigms: GTEP: Other
Abstract
Correlated equilibria are a standard solution concept in game theory and generalize Nash equilibria. In a 2-player non-cooperative game in which player i has action set A_i, a correlated equilibrium is a self-enforcing probability distribution σ over A_1 * A_2. Specifically, when a strategy profile (s_1, s_2) in A_1 * A_2 is sampled according to σ, each player i can observe their own component s_i, but not the other player's component. Knowing s_i and σ, player i cannot increase their expected payoff by defecting and playing a strategy s'_i different from s_i. Correlated equilibria are ubiquitous and crucial in mechanism design, including in the design of blockchain-based protocols which aim to incentivize honest behavior.
A correlated equilibrium depends on a centralized and impartial oracle, often called the ''external signal'' in game theory literature, to sample a strategy profile and disclose each player's component to them, while keeping the other player's component secret. However, there is currently no trustless method to achieve this on the blockchain without centralization or relying on trusted third-parties.
In this work, we address this challenge and provide two novel protocols, one based on oblivious transfer and the other based on zkSNARKs to replace the public signal with a smart contract. We prove that our approaches are secure and provide the desired privacy properties of a correlated equilibrium, while also being efficient in terms of gas usage and thus affordable in practice.
@inproceedings{ijcai2025p416,
title = {Smart Contracts for Trustless Sampling of Correlated Equilibria},
author = {Barakbayeva, Togzhan and Cai, Zhuo and Goharshady, Amir and Keypoor, Karaneh},
booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-25}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {James Kwok},
pages = {3744--3752},
year = {2025},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2025/416},
url = {https://doi.org/10.24963/ijcai.2025/416},
}
TY - CPAPER TI - Smart Contracts for Trustless Sampling of Correlated Equilibria AU - Barakbayeva, Togzhan AU - Cai, Zhuo AU - Goharshady, Amir AU - Keypoor, Karaneh T2 - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2025 SP - 3744 EP - 3752 DO - 10.24963/ijcai.2025/416 UR - https://doi.org/10.24963/ijcai.2025/416 ER -Copied
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