RPPLNS: Pay-per-last-N-shares with a Randomised Twist

no code implementations • 15 Feb 2021 • Jonathan Katz, Philip Lazos, Francisco J. Marmolejo-Cossío, Xinyu Zhou

"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

Optimally Deceiving a Learning Leader in Stackelberg Games

no code implementations • NeurIPS 2020 • Georgios Birmpas, Jiarui Gan, Alexandros Hollender, Francisco J. Marmolejo-Cossío, Ninad Rajgopal, Alexandros A. Voudouris

For this strategic behavior to be successful, the main challenge faced by the follower is to pinpoint the payoffs that would make the learning algorithm compute a commitment so that best responding to it maximizes the follower's utility, according to his true payoffs.

Learning Convex Partitions and Computing Game-theoretic Equilibria from Best Response Queries

no code implementations • 17 Jul 2018 • Paul W. Goldberg, Francisco J. Marmolejo-Cossío

Suppose that an $m$-simplex is partitioned into $n$ convex regions having disjoint interiors and distinct labels, and we may learn the label of any point by querying it.