Game theory is the study of strategic decision-making where the outcome for each participant is contingent upon the choices made by all involved parties. In the context of digital assets and blockchain, game theory is instrumental in designing incentive structures, consensus mechanisms, and economic models that encourage rational actors to behave in ways beneficial to the network. It aids in predicting participant conduct and ensuring the integrity of decentralized systems.
Context
Game theory plays a pivotal role in the design and analysis of blockchain protocols, particularly in aligning incentives for network participants such as miners, validators, and users. Current discussions frequently address the refinement of consensus algorithms, like Proof-of-Stake, to ensure individual incentives align with collective network security and efficiency, thereby addressing potential game-theoretic vulnerabilities.
This research introduces a novel transaction fee mechanism, overcoming a foundational impossibility theorem to ensure miner incentives and user truthfulness in blockchain networks.
This research establishes a formal theory for Maximal Extractable Value (MEV), providing a foundational framework to analyze and mitigate economic attacks on public blockchains.
This research leverages game theory to model Maximal Extractable Value dynamics, proposing commit-reveal and threshold encryption mechanisms to enhance DeFi fairness.
This research establishes a rigorous theoretical framework for Maximal Extractable Value, enabling provably secure mitigation strategies for blockchain vulnerabilities.
This research formalizes MEV extraction as a multi-stage game, revealing systemic welfare losses and proposing cryptographic mechanisms to restore market fairness.
This paper establishes a rigorous, abstract framework for Maximal Extractable Value, enabling systematic analysis and robust defenses against economic exploits in decentralized systems.
This research establishes a foundational framework for analyzing the economic security of blockchain consensus protocols, quantifying attack costs to enable more robust designs.
This research formally models MEV as a multi-stage game, revealing competitive dynamics that degrade welfare and quantifies mitigation through commit-reveal schemes.
This theory formally defines Maximal Extractable Value, offering a robust framework for proving smart contract security and clarifying adversarial extraction in blockchains.
This research introduces revelation mechanisms within Proof-of-Stake protocols, fundamentally addressing consensus disputes by incentivizing truthful block proposals.
This research formalizes Maximal Extractable Value dynamics through a multi-stage game, revealing systemic inefficiencies and quantifying mitigation strategies.
This research establishes a universal, game-theoretic definition for Maximal Extractable Value, fundamentally reframing economic attacks within public blockchains for systematic mitigation.
This research formalizes Maximal Extractable Value, providing a rigorous framework for understanding and mitigating systemic blockchain vulnerabilities.
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