# Revac: A Social Deduction Reasoning Agent

arXiv: https://arxiv.org/abs/2604.19523 · HTML: https://mlsanity.com/paper/2604.19523/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 10 references that are in the map.
- First posted on arXiv 21 Apr 2026.

## Builds on (most cited first, 7 of 7)

- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Theory of Mind for Multi-Agent Collaboration via Large Language Models](https://mlsanity.com/paper/2310.10701/) (2023)
- [Playing the Werewolf game with artificial intelligence for language understanding](https://mlsanity.com/paper/2302.10646/) (2023)
- [Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2502.06060/) (2025)
- [RLupus: Cooperation through emergent communication in The Werewolf social deduction game](https://mlsanity.com/paper/2106.05018/) (2021)
- [Enhancing Dialogue Generation in Werewolf Game Through Situation Analysis and Persuasion Strategies](https://mlsanity.com/paper/2408.16586/) (2024)

## Abstract (arXiv)

Social deduction games such as Mafia present a unique AI challenge: players must reason under uncertainty, interpret incomplete and intentionally misleading information, evaluate human-like communication, and make strategic elimination decisions. Unlike deterministic board games, success in Mafia depends not on perfect information or brute-force search, but on inference, memory, and adaptability in the presence of deception. This work presents the design and evaluation of Revac-8, an AI agent developed for the Social Deduction track of the MindGames Arena competition, where it achieved first place. The final agent evolved from a simple two-stage reasoning system into a multi-module architecture that integrates memory-based player profiling, social-graph analysis of accusations and defenses, and dynamic tone selection for communication. These results highlight the importance of structured memory and adaptive communication for achieving strong performance in high-stakes social environments.