# Active Inference for an Intelligent Agent in Autonomous Reconnaissance Missions

arXiv: https://arxiv.org/abs/2510.17450 · HTML: https://mlsanity.com/paper/2510.17450/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 33 references that are in the map.
- First posted on arXiv 20 Oct 2025.

## Builds on (most cited first, 14 of 14)

- [The free energy principle for action and perception: A mathematical review](https://mlsanity.com/paper/1705.09156/) (2017)
- [Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics](https://mlsanity.com/paper/2011.09756/) (2020)
- [Multimodal VAE Active Inference Controller](https://mlsanity.com/paper/2103.04412/) (2021)
- [A Novel Adaptive Controller for Robot Manipulators based on Active Inference](https://mlsanity.com/paper/1909.12768/) (2019)
- [Free Energy Principle for State and Input Estimation of a Quadcopter Flying in Wind](https://mlsanity.com/paper/2109.12052/) (2021)
- [Adaptation through prediction: multisensory active inference torque control](https://mlsanity.com/paper/2112.06752/) (2021)
- [Active Inference for Autonomous Decision-Making with Contextual Multi-Armed Bandits](https://mlsanity.com/paper/2209.09185/) (2022)
- [Application of the Free Energy Principle to Estimation and Control](https://mlsanity.com/paper/1910.09823/) (2019)
- [Fault-tolerant Control of Robot Manipulators with Sensory Faults using Unbiased Active Inference](https://mlsanity.com/paper/2104.01817/) (2021)
- [Multi-Agent Deep Reinforcement Learning For Persistent Monitoring With Sensing, Communication, and Localization Constraints](https://mlsanity.com/paper/2109.06831/) (2021)
- [Multi-Agent Reinforcement Learning for Visibility-based Persistent Monitoring](https://mlsanity.com/paper/2011.01129/) (2020)
- [Nonmodular architectures of cognitive systems based on active inference](https://mlsanity.com/paper/1903.09542/) (2019)
- [Inference of Affordances and Active Motor Control in Simulated Agents](https://mlsanity.com/paper/2202.11532/) (2022)
- [Active Inference in Contextual Multi-Armed Bandits for Autonomous Robotic Exploration](https://mlsanity.com/paper/2408.04119/) (2024)

## Abstract (arXiv)

We develop an active inference route-planning method for the autonomous control of intelligent agents. The aim is to reconnoiter a geographical area to maintain a common operational picture. To achieve this, we construct an evidence map that reflects our current understanding of the situation, incorporating both positive and "negative" sensor observations of possible target objects collected over time, and diffusing the evidence across the map as time progresses. The generative model of active inference uses Dempster-Shafer theory and a Gaussian sensor model, which provides input to the agent. The generative process employs a Bayesian approach to update a posterior probability distribution. We calculate the variational free energy for all positions within the area by assessing the divergence between a pignistic probability distribution of the evidence map and a posterior probability distribution of a target object based on the observations, including the level of surprise associated with receiving new observations. Using the free energy, we direct the agents' movements in a simulation by taking an incremental step toward a position that minimizes the free energy. This approach addresses the challenge of exploration and exploitation, allowing agents to balance searching extensive areas of the geographical map while tracking identified target objects.