Revac: A Social Deduction Reasoning Agent

Mihir Shriniwas Arya, Avinash Anish, Aditya Ranjan
4/21/2026
cs.AI

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Abstract

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.

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Cite this paper

@article{arya2026revac,
  title  = {Revac: A Social Deduction Reasoning Agent},
  author = {Mihir Shriniwas Arya and Avinash Anish and Aditya Ranjan},
  year   = {2026},
  eprint = {2604.19523},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2604.19523v1}
}

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