How to make robots explain their decisions?
HARMONIC: A Framework for Explanatory Cognitive Robots
September 27, 2024
https://arxiv.org/pdf/2409.18037This paper introduces HARMONIC, a framework for building robots that can understand and respond to requests, explain their actions, and collaborate with humans.
Here's how it relates to LLM-based multi-agent systems:
- Dual Control System: HARMONIC uses a "strategic" layer (for high-level reasoning, potentially using LLMs) and a "tactical" layer (for robot control). This split is key for integrating LLMs into real-world applications where they can't directly control actions.
- Explainability: The paper highlights the need for robots to explain their actions to build trust. While LLMs alone aren't great at providing transparent reasoning, HARMONIC suggests limiting them to specific modules within the framework to improve explainability.
- Knowledge Bases: HARMONIC relies on ontologies, lexicons, and agent profiles to give robots the background knowledge needed for understanding requests and reasoning about the world. This suggests that LLM-based agents would benefit from well-structured external knowledge sources.