# Neural Amortized Inference for Nested Multi-agent Reasoning

arXiv: https://arxiv.org/abs/2308.11071 · HTML: https://mlsanity.com/paper/2308.11071/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 21 references that are in the map.
- First posted on arXiv 21 Aug 2023.

## Builds on (most cited first, 9 of 9)

- [Cooperative Inverse Reinforcement Learning](https://mlsanity.com/paper/1606.03137/) (2016)
- [Machine Theory of Mind](https://mlsanity.com/paper/1802.07740/) (2018)
- [Inference Compilation and Universal Probabilistic Programming](https://mlsanity.com/paper/1610.09900/) (2016)
- [Theory of Minds: Understanding Behavior in Groups Through Inverse Planning](https://mlsanity.com/paper/1901.06085/) (2019)
- [Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving](https://mlsanity.com/paper/2007.00178/) (2020)
- [PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception](https://mlsanity.com/paper/2103.01933/) (2021)
- [Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale](https://mlsanity.com/paper/1907.03382/) (2019)
- [Monte Carlo Sampling Methods for Approximating Interactive POMDPs](https://mlsanity.com/paper/1401.3455/) (2014)
- [Nested Reasoning About Autonomous Agents Using Probabilistic Programs](https://mlsanity.com/paper/1812.01569/) (2018)

## Built on by (most cited first, 8 of 8)

- [Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning](https://mlsanity.com/paper/2312.05230/) (2023)
- [MuMA-ToM: Multi-modal Multi-Agent Theory of Mind](https://mlsanity.com/paper/2408.12574/) (2024)
- [AutoToM: Scaling Model-based Mental Inference via Automated Agent Modeling](https://mlsanity.com/paper/2502.15676/) (2025)
- [Modeling Others' Minds as Code](https://mlsanity.com/paper/2510.01272/) (2025)
- [Grounding Social Perception in Intuitive Physics](https://mlsanity.com/paper/2603.27410/) (2026)
- [Agentic Meta-Orchestrator for Multi-task Copilots](https://mlsanity.com/paper/2510.22781/) (2025)
- [MindZero: Learning Online Mental Reasoning With Zero Annotations](https://mlsanity.com/paper/2606.00240/) (2026)
- [Tapes Together Strong: The Co-evolution of Computation and Cooperation](https://mlsanity.com/paper/2609.10817/) (2026)

## Abstract (arXiv)

Multi-agent interactions, such as communication, teaching, and bluffing, often rely on higher-order social inference, i.e., understanding how others infer oneself. Such intricate reasoning can be effectively modeled through nested multi-agent reasoning. Nonetheless, the computational complexity escalates exponentially with each level of reasoning, posing a significant challenge. However, humans effortlessly perform complex social inferences as part of their daily lives. To bridge the gap between human-like inference capabilities and computational limitations, we propose a novel approach: leveraging neural networks to amortize high-order social inference, thereby expediting nested multi-agent reasoning. We evaluate our method in two challenging multi-agent interaction domains. The experimental results demonstrate that our method is computationally efficient while exhibiting minimal degradation in accuracy.