GTAIMAGNNov 29, 2019

Heuristic Strategies in Uncertain Approval Voting Environments

arXiv:1912.00011v12 citations
Originality Synthesis-oriented
AI Analysis

This addresses strategic voting challenges for agents in collective decision-making, but it is incremental as it builds on existing work in voting theory.

The paper tackled the problem of how voters use heuristics like truth-telling or prioritizing high-utility candidates in approval voting with missing votes, showing through a behavioral experiment that these behaviors maximize expected utility depending on the voting environment structure.

In many collective decision making situations, agents vote to choose an alternative that best represents the preferences of the group. Agents may manipulate the vote to achieve a better outcome by voting in a way that does not reflect their true preferences. In real world voting scenarios, people often do not have complete information about other voter preferences and it can be computationally complex to identify a strategy that will maximize their expected utility. In such situations, it is often assumed that voters will vote truthfully rather than expending the effort to strategize. However, being truthful is just one possible heuristic that may be used. In this paper, we examine the effectiveness of heuristics in single winner and multi-winner approval voting scenarios with missing votes. In particular, we look at heuristics where a voter ignores information about other voting profiles and makes their decisions based solely on how much they like each candidate. In a behavioral experiment, we show that people vote truthfully in some situations and prioritize high utility candidates in others. We examine when these behaviors maximize expected utility and show how the structure of the voting environment affects both how well each heuristic performs and how humans employ these heuristics.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes