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Found 6 papers, 0 papers with code
Would Friedman Burn your Tokens?
Cryptocurrencies come with a variety of tokenomic policies as well as aspirations of desirable monetary characteristics that have been described by proponents as 'sound money' or even 'ultra sound money.'
Allocating Indivisible Goods to Strategic Agents: Pure Nash Equilibria and Fairness
For Round-Robin we show that all of its pure Nash equilibria induce allocations that are EF1 with respect to the underlying true values, while for the algorithm of Plaut and Roughgarden we show that the corresponding allocations not only are EFX but also satisfy maximin share fairness, something that is not true for this algorithm in the non-strategic setting!
On the Complexity of Equilibrium Computation in First-Price Auctions
We consider the problem of computing a (pure) Bayes-Nash equilibrium in the first-price auction with continuous value distributions and discrete bidding space.
Computer Science and Game Theory Computational Complexity
Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
Submodular maximization is a classic algorithmic problem with multiple applications in data mining and machine learning; there, the growing need to deal with massive instances motivates the design of algorithms balancing the quality of the solution with applicability.
RPPLNS: Pay-per-last-N-shares with a Randomised Twist
"Pay-per-last-$N$-shares" (PPLNS) is one of the most common payout strategies used by mining pools in Proof-of-Work (PoW) cryptocurrencies.
Fairness
Computer Science and Game Theory
Cryptography and Security
Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint
Constrained submodular maximization problems encompass a wide variety of applications, including personalized recommendation, team formation, and revenue maximization via viral marketing.
