Autonomous Penetration Testing using Reinforcement Learning. - Jonathon Schwartz; Hanna Kurniawati (CoRR, 2019)

POMDP + Information-Decay: Incorporating Defender's Behaviour in Autonomous Penetration Testing. - Jonathon Schwartz; Hanna Kurniawati; Edwin El-Mahassni (ICAPS, 2020)

CybORG: An Autonomous Cyber Operations Research Gym. - Callum Baillie; Maxwell Standen; Jonathon Schwartz; Michael Docking; David Bowman; Junae Kim (CoRR, 2020)

Online Planning for Interactive-POMDPs using Nested Monte Carlo Tree Search. - Jonathon Schwartz; Ruijia Zhou; Hanna Kurniawati (IROS, 2022)

Towards Scalable and Robust Decision Making in Partially Observable, Multi-Agent Environments. - Jonathon Schwartz (AAMAS, 2023)

Bayes-Adaptive Monte-Carlo Planning for Type-Based Reasoning in Large Partially Observable, Multi-Agent Environments. - Jonathon Schwartz; Hanna Kurniawati (AAMAS, 2023)

Combining a Meta-Policy and Monte-Carlo Planning for Scalable Type-Based Reasoning in Partially Observable Environments. - Jonathon Schwartz; Hanna Kurniawati; Marcus Hutter (CoRR, 2023)

The utility of generative artificial intelligence Chatbot (ChatGPT) in generating teaching and learning material for anesthesiology residents. - Zhaosheng Jin; Ramon Abola; Vincent Bargnes; Alexandra Tsivitis; Sadiq Rahman; Jonathon Schwartz; Sergio D. Bergese; Joy E. Schabel (Frontiers Artif. Intell., 2025)

POSGGym: a library for decision-theoretic planning and learning in partially observable, multi-agent environments. - Jonathon Schwartz; Rhys Newbury; Dana Kulic; Hanna Kurniawati (Auton. Agents Multi Agent Syst., 2025)