This project was funded within the Distributed Analytics & Information Sciences International Technology Alliance (DAIS-ITA) programme between the UK MoD and US ARL. The goal of this project was to develop techniques and tools to aid the efficient deployment, management, and operation of coalition networks in complex environments. Specifically, we focused on the challenge of learning interpretable knowledge in a symbolic form, to enable robustness guarantees and interoperability between coalition partners. SPIKE Imperial collaborated closely with Purdue University, IBM, and our government clients to develop a suite of tools surrounding logic-based machine learning, capable of tackling event detection, network intrusion, and policy learning tasks. Our main achievement was developing the FastLAS tool for symbolic machine learning, which was designated a programme highlight. Please refer to https://dais-legacy.org/1c02/ for an applied demonstration.