Prior work on the complexity of bribery assumes that the bribery happens simultaneously, and that the briber has full knowledge of all voters' votes. But neither of those assumptions always holds. In many real-world settings, votes come in sequentially, and the briber may have a use-it-or-lose-it moment to decide whether to bribe alter a given vote, and at the time of making that decision, the briber may not know what votes remaining voters are planning on casting. In this paper, we introduce a model for, and initiate the study of, bribery in such an online, sequential setting. We show that even for election systems whose winner-determination problem is polynomial-time computable, an online, sequential setting may vastly increase the complexity of bribery, in fact jumping the problem up to completeness for high levels of the polynomial hierarchy or even PSPACE. On the other hand, we show that for some natural, important election systems, such a dramatic complexity increase does not occur, and we pinpoint the complexity of their bribery problems in the online, sequential setting.
Preface 1. Introduction to competitive analysis: the list accessing problem 2. Introduction to randomized algorithms: the list accessing problem 3. Paging: deterministic algorithms 4. Paging: randomized algorithms 5. Alternative models for paging: beyond pure competitive analysis 6. Game theoretic foundations 7. Request - answer games 8. Competitive analysis and zero-sum games 9. Metrical task systems 10. The k-server problem 11. Randomized k-server algorithms 12. Load-balancing 13. Call admission and circuit-routing 14. Search, trading and portfolio selection 15. Competitive analysis and decision making under uncertainty Appendices Bibliography Index.