# IKT-BT: Indirect Knowledge Transfer Behavior Tree Framework for Multi-Robot Systems Through Communication Eavesdropping

arXiv: https://arxiv.org/abs/2312.11802 · HTML: https://mlsanity.com/paper/2312.11802/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Dec 2023.

## Built on by (most cited first, 2 of 2)

- [HARMONIC: A Framework for Explanatory Cognitive Robots](https://mlsanity.com/paper/2409.18037/) (2024)
- [HARMONIC: Cognitive and Control Collaboration in Human-Robotic Teams](https://mlsanity.com/paper/2409.18047/) (2024)

## Abstract (arXiv)

Multi-agent and multi-robot systems (MRS) often rely on direct communication for information sharing. This work explores an alternative approach inspired by eavesdropping mechanisms in nature that involves casual observation of agent interactions to enhance decentralized knowledge dissemination. We achieve this through a novel IKT-BT framework tailored for a behavior-based MRS, encapsulating knowledge and control actions in Behavior Trees (BT). We present two new BT-based modalities - eavesdrop-update (EU) and eavesdrop-buffer-update (EBU) - incorporating unique eavesdropping strategies and efficient episodic memory management suited for resource-limited swarm robots. We theoretically analyze the IKT-BT framework for an MRS and validate the performance of the proposed modalities through extensive experiments simulating a search and rescue mission. Our results reveal improvements in both global mission performance outcomes and agent-level knowledge dissemination with a reduced need for direct communication.