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20092026
most citedHow To Grade a Test Without Knowing the Answers --- A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing

113 citations · 399 across the 53 of their papers we have counts for

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13 papers · 1 filter

cs.GT2024

Approximating the Core via Iterative Coalition Sampling

Ian Gemp, Marc Lanctot, Luke Marris +11

The core is a central solution concept in cooperative game theory, defined as the set of feasible allocations or payments such that no subset of agents has incentive to break away…

cs.GT2021

Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent

Ian Gemp, Rahul Savani, Marc Lanctot +6

Nash equilibrium is a central concept in game theory. Several Nash solvers exist, yet none scale to normal-form games with many actions and many players, especially those with payo…

cs.GT2020

Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games

Edward Hughes, Thomas W. Anthony, Tom Eccles +3

Zero-sum games have long guided artificial intelligence research, since they possess both a rich strategy space of best-responses and a clear evaluation metric. What's more, compet…

cs.GT2017

Agent Failures in All-Pay Auctions

Yoad Lewenberg, Omer Lev, Yoram Bachrach +1

All-pay auctions, a common mechanism for various human and agent interactions, suffers, like many other mechanisms, from the possibility of players' failure to participate in the a…

cs.GT2014★ 3 cited

Power Distribution in Randomized Weighted Voting: the Effects of the Quota

Joel Oren, Yuval Filmus, Yair Zick +1

We study the Shapley value in weighted voting games. The Shapley value has been used as an index for measuring the power of individual agents in decision-making bodies and politica…

cs.GT2014★ 1 cited

Optimising Trade-offs Among Stakeholders in Ad Auctions

Yoram Bachrach, Sofia Ceppi, Ian A. Kash +2

We examine trade-offs among stakeholders in ad auctions. Our metrics are the revenue for the utility of the auctioneer, the number of clicks for the utility of the users and the we…