Strategic Manipulation in Temporal Voting with Undesirable Candidates (Student Abstract) - Neoh, Tzeh Yuan; Teh, Nicholas (Proceedings of the AAAI Conference on Artificial Intelligence, 2025)
We study a model of sequential decision-making where voters have dynamic preferences over a set of candidates that are undesirable. This models scenarios such as the implementation of projects that are overall beneficial to society, but impose individual costs on certain affected individuals. We show that while minimizing the sum of agents' disutilities can be done in polynomial time, minimizing the maximum disutility obtained by any agent is computationally intractable, even in restricted cases. We then examine the potential for agents to engage in strategic manipulation in response to these welfare objectives, offering insights into possible misconduct within such decision-making environments.