# Pandering in a Flexible Representative Democracy

arXiv: https://arxiv.org/abs/2211.09986 · HTML: https://mlsanity.com/paper/2211.09986/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 58 references that are in the map.
- First posted on arXiv 18 Nov 2022.

## Builds on (most cited first, 13 of 13)

- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Playing Atari with Deep Reinforcement Learning](https://mlsanity.com/paper/1312.5602/) (2013)
- [Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments](https://mlsanity.com/paper/1706.02275/) (2017)
- [Dota 2 with Large Scale Deep Reinforcement Learning](https://mlsanity.com/paper/1912.06680/) (2019)
- [Justified Representation in Approval-Based Committee Voting](https://mlsanity.com/paper/1407.8269/) (2014)
- [Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology](https://mlsanity.com/paper/1905.12767/) (2019)
- [Multi-agent Reinforcement Learning in Bayesian Stackelberg Markov Games for Adaptive Moving Target Defense](https://mlsanity.com/paper/2007.10457/) (2020)
- [The Fluid Mechanics of Liquid Democracy](https://mlsanity.com/paper/1808.01906/) (2018)
- [On Rational Delegations in Liquid Democracy](https://mlsanity.com/paper/1802.08020/) (2018)
- [Power in Liquid Democracy](https://mlsanity.com/paper/2010.07070/) (2020)
- [Flexible Representative Democracy: An Introduction with Binary Issues](https://mlsanity.com/paper/1811.02921/) (2018)
- [Spatial-Temporal Moving Target Defense: A Markov Stackelberg Game Model](https://mlsanity.com/paper/2002.10390/) (2020)
- [Complexity of Shift Bribery in Committee Elections](https://mlsanity.com/paper/1601.01492/) (2016)

## Abstract (arXiv)

In representative democracies, the election of new representatives in regular election cycles is meant to prevent corruption and other misbehavior by elected officials and to keep them accountable in service of the ``will of the people." This democratic ideal can be undermined when candidates are dishonest when campaigning for election over these multiple cycles or rounds of voting. Much of the work on COMSOC to date has investigated strategic actions in only a single round. We introduce a novel formal model of pandering, or strategic preference reporting by candidates seeking to be elected, and examine the resilience of two democratic voting systems to pandering within a single round and across multiple rounds. The two voting systems we compare are Representative Democracy (RD) and Flexible Representative Democracy (FRD). For each voting system, our analysis centers on the types of strategies candidates employ and how voters update their views of candidates based on how the candidates have pandered in the past. We provide theoretical results on the complexity of pandering in our setting for a single cycle, formulate our problem for multiple cycles as a Markov Decision Process, and use reinforcement learning to study the effects of pandering by both single candidates and groups of candidates across a number of rounds.