Efficient probabilistically checkable proofs and applications to approximations
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Winner determination in combinatorial auction generalizations
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
The turing way to parameterized complexity
Journal of Computer and System Sciences - Special issue on Parameterized computation and complexity
Parameterized Complexity
How hard is it to bribe the judges? a study of the complexity of bribery in judgment aggregation
ADT'11 Proceedings of the Second international conference on Algorithmic decision theory
Determining possible and necessary winners under common voting rules given partial orders
Journal of Artificial Intelligence Research
Cloning in elections: finding the possible winners
Journal of Artificial Intelligence Research
Cecision making under uncertainty: social choice and manipulation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Studies in computational aspects of voting: open problems of downey and fellows
The Multivariate Algorithmic Revolution and Beyond
Complexity of optimal lobbying in threshold aggregation
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
A behavioral perspective on social choice
Annals of Mathematics and Artificial Intelligence
Bribery in voting with CP-nets
Annals of Mathematics and Artificial Intelligence
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We propose various models for lobbying in a probabilistic environment, in which an actor (called "The Lobby") seeks to influence the voters' preferences of voting for or against multiple issues when the voters' preferences are represented in terms of probabilities. In particular, we provide two evaluation criteria and three bribery methods to formally describe these models, and we consider the resulting forms of lobbying with and without issue weighting. We provide a formal analysis for these problems of lobbying in a stochastic environment, and determine their classical and parameterized complexity depending on the given bribery/evaluation criteria. Specifically, we show that some of these problems can be solved in polynomial time, some are NP-complete but fixed-parameter tractable, and some are W[2]-complete. Finally, we provide (in)approximability results.