A Stackelberg Game is a model of sequential decision-making in game theory where one player, the leader, moves first and commits to a strategy, and subsequent players, the followers, observe the leader’s action and then choose their own optimal strategies. The leader anticipates the followers’ reactions and makes their initial move to maximize their own payoff, knowing how the followers will respond. This structure is common in economic competition.
Context
In the cryptocurrency domain, Stackelberg Game dynamics can be observed in scenarios involving protocol upgrades, token distribution strategies, or the competitive actions of decentralized exchanges. Discussions often analyze how early movers in a particular market segment can influence the behavior of later entrants. Understanding these game-theoretic interactions is vital for predicting market outcomes and strategic decision-making by protocol developers and large token holders.
This research introduces a Stackelberg game model and ADMM algorithm to motivate edge servers, enabling optimal resource contribution in decentralized AI training.
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