# Robot Metacognition: Decision Making with Confidence for Tool Invention

arXiv: https://arxiv.org/abs/2511.16390 · HTML: https://mlsanity.com/paper/2511.16390/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 27 references that are in the map.
- First posted on arXiv 20 Nov 2025.

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

- [On Calibration of Modern Neural Networks](https://mlsanity.com/paper/1706.04599/) (2017)
- [Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods](https://mlsanity.com/paper/1910.09457/) (2019)
- [Feedback Efficient Online Fine-Tuning of Diffusion Models](https://mlsanity.com/paper/2402.16359/) (2024)
- [Supervised structure learning](https://mlsanity.com/paper/2311.10300/) (2023)
- [Learning to Design and Use Tools for Robotic Manipulation](https://mlsanity.com/paper/2311.00754/) (2023)
- [Diffusion Generative Inverse Design](https://mlsanity.com/paper/2309.02040/) (2023)
- [Confidence-Aware Decision-Making and Control for Tool Selection](https://mlsanity.com/paper/2403.03808/) (2024)
- [Understanding Tool Discovery and Tool Innovation Using Active Inference](https://mlsanity.com/paper/2311.03893/) (2023)
- [Designing Tools with Control Confidence](https://mlsanity.com/paper/2510.12630/) (2025)

## Abstract (arXiv)

Robots today often miss a key ingredient of truly intelligent behavior: the ability to reflect on their own cognitive processes and decisions. In humans, this self-monitoring or metacognition is crucial for learning, decision making and problem solving. For instance, they can evaluate how confident they are in performing a task, thus regulating their own behavior and allocating proper resources. Taking inspiration from neuroscience, we propose a robot metacognition architecture centered on confidence (a second-order judgment on decisions) and we demonstrate it on the use case of autonomous tool invention. We propose the use of confidence as a metacognitive measure within the robot decision making scheme. Confidence-informed robots can evaluate the reliability of their decisions, improving their robustness during real-world physical deployment. This form of robotic metacognition emphasizes embodied action monitoring as a means to achieve better informed decisions. We also highlight potential applications and research directions for robot metacognition.