Robot Metacognition: Decision Making with Confidence for Tool Invention

TL;DR

This paper introduces a robot metacognition framework based on confidence, enabling robots to assess decision reliability, which enhances robustness and decision-making in autonomous tool invention tasks.

Contribution

It presents a novel confidence-based metacognition architecture inspired by neuroscience, applied to autonomous tool invention, improving robot decision robustness.

Findings

Confidence improves decision reliability in robots.

Metacognitive architecture enhances robustness during physical deployment.

Application demonstrated in autonomous tool invention.

Abstract

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.