Anyone but him: The complexity of precluding an alternative
Artificial Intelligence
Winner determination in sequential majority voting
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Manipulating Tournaments in Cup and Round Robin Competitions
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
Designing competitions between teams of individuals
Artificial Intelligence
Fair Seeding in Knockout Tournaments
ACM Transactions on Intelligent Systems and Technology (TIST)
Is computational complexity a barrier to manipulation?
Annals of Mathematics and Artificial Intelligence
Winner determination in voting trees with incomplete preferences and weighted votes
Autonomous Agents and Multi-Agent Systems
Manipulating stochastically generated single-elimination tournaments for nearly all players
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
An empirical study of seeding manipulations and their prevention
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
On the evaluation of election outcomes under uncertainty
Artificial Intelligence
AT'13 Proceedings of the Second international conference on Agreement Technologies
From blurry numbers to clear preferences: A mechanism to extract reputation in social networks
Expert Systems with Applications: An International Journal
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Knockout tournaments constitute a common format of sporting events, and also model a specific type of election scheme (namely, sequential pairwise elimination election). In such tournaments the designer controls the shape of the tournament (a binary tree) and the seeding of the players (their assignment to the tree leaves). In this paper we investigate the computational complexity of tournament schedule control, i.e., designing a tournament that maximizes the winning probability a target player. We start with a generic probabilistic model consisting of a matrix of pairwise winning probabilities, and then investigate the problem under two types of constraint: constraints on the probability matrix, and constraints on the allowable tournament structure. While the complexity of the general problem is as yet unknown, these various constraints -- all naturally occurring in practice -- serve to push to the problem to one side or the other: easy (polynomial) or hard (NP-complete).