J
John J. Bartholdi
Researcher at Georgia Institute of Technology
Publications - 72
Citations - 5687
John J. Bartholdi is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Scheduling (computing) & Heuristic. The author has an hindex of 36, co-authored 72 publications receiving 5399 citations.
Papers
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Journal ArticleDOI
The computational difficulty of manipulating an election
TL;DR: A voting rule is exhibited that efficiently computes winners but is computationally resistant to strategic manipulation, showing how computational complexity might protect the integrity of social choice.
Journal ArticleDOI
Voting schemes for which it can be difficult to tell who won the election
TL;DR: It is shown that a voting scheme suggested by Lewis Carroll can be impractical in that it can be computationally prohibitive to determine whether any particular candidate has won an election, and a class of "impracticality theorems" are suggested which say that any fair voting scheme must, in the worst-case, require excessive computation to determine a winner.
Journal ArticleDOI
How hard is it to control an election
TL;DR: In this paper, the authors show that some voting schemes that are in principle susceptible to control are nevertheless resistant in practice due to excessive computational costs; others are vulnerable due to their computational complexity.
Book
Single Transferable Vote Resists Strategic Voting
John J. Bartholdi,James B. Orlin +1 more
TL;DR: Evidence that Single Tranferable Vote (STV) is computationally resistant to manipulation is given and it is proved that it is NP-complete to recognize when an STV election violates monotonicity, suggesting that non-monotonicity in STV elections might be perceived as less threatening since it is in effect “hidden” and hard to exploit for strategic advantage.
Journal ArticleDOI
A Production Line that Balances Itself
TL;DR: This analysis suggests and experiments confirm that if the workers are sequenced from slowest to fastest then, independently of the stations at which they begin, a stable partition of work will spontaneously emerge and the production rate will converge to a value that is the maximum possible among all ways of organizing the workers and stations.