Artificial Intelligence
Asymptotic and finite size parameters for phase transitions: Hamiltonian circuit as a case study
Information Processing Letters
The constrainedness knife-edge
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Beyond NP: the QSAT phase transition
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Morphing: combining structure and randomness
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
A physicist's approach to number partitioning
Theoretical Computer Science - Phase transitions in combinatorial problems
Scaling Effects in the CSP Phase Transition
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
When are elections with few candidates hard to manipulate?
Journal of the ACM (JACM)
A sufficient condition for voting rules to be frequently manipulable
Proceedings of the 9th ACM conference on Electronic commerce
Complexity of terminating preference elicitation
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Manipulation and gender neutrality in stable marriage procedures
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Uncertainty in preference elicitation and aggregation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Phase transitions and backbones of the asymmetric traveling salesman problem
Journal of Artificial Intelligence Research
The Gn,mphase transition is not hard for the Hamiltonian cycle problem
Journal of Artificial Intelligence Research
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Where the really hard problems are
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Phase transitions of PP-complete satisfiability problems
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Where are the really hard manipulation problems? the phase transition in manipulating the veto rule
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Complexity of unweighted coalitional manipulation under some common voting rules
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Manipulating Tournaments in Cup and Round Robin Competitions
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
An Empirical Study of the Manipulability of Single Transferable Voting
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Unweighted coalitional manipulation under the Borda rule Is NP-hard
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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When agents are acting together, they may need a simple mechanism to decide on joint actions. One possibility is to have the agents express their preferences in the form of a ballot and use a voting rule to decide the winning action(s). Unfortunately, agents may try to manipulate such an election by misreporting their preferences. Fortunately, it has been shown that it is NP-hard to compute how to manipulate a number of different voting rules. However, NP-hardness only bounds the worst-case complexity. Recent theoretical results suggest that manipulation may often be easy in practice. To address this issue, I suggest studying empirically if computational complexity is in practice a barrier to manipulation. The basic tool used in my investigations is the identification of computational "phase transitions". Such an approach has been fruitful in identifying hard instances of propositional satisfiability and other NP-hard problems. I show that phase transition behaviour gives insight into the hardness of manipulating voting rules, increasing concern that computational complexity is indeed any sort of barrier. Finally, I look at the problem of computing manipulation of other, related problems like stable marriage and tournament problems.