Rate My Professor Michael Barlow

Professor Michael Barlow is a Professor in the School of Systems and Computing at UNSW Canberra, University of New South Wales. He possesses over 30 years of experience in artificial intelligence and machine learning, encompassing decision-support, simulation, multi-agent systems, reinforcement learning, deployment of Large Language Models, and Serious Games. As the co-founder and director of the Intelligent Systems for State and Societal Resilience (IS4SSR) Hub, he oversees a team that co-designs and builds digital solutions for partners working in complex, contested spaces. Key priorities of the hub include women's and children's safety, individual well-being, and community resilience. Barlow has been with UNSW Canberra for more than 25 years. He previously served as Acting Head of the School of Engineering and Information Technology, Deputy Head of School for People, and has held a range of other leadership roles since 2006. He is proud of mentoring higher degree by research students and teaching undergraduates across his career.

Barlow's scholarly output includes numerous publications in leading journals. Select journal articles are: Bagheri N, Ghasri M, Barlow M (2025), 'A neural estimation framework for discrete choice models with arbitrary error distributions', Journal of Choice Modelling, 57; Arukgoda A et al. (2024), 'Effective Motive Profile Compositions for Cooperative Ad-Hoc Teams', IEEE Transactions on Cognitive and Developmental Systems, 16, pp. 1027-1040; Kasmarik K et al. (2024), 'Competence Awareness for Humans and Machines: A Survey and Future Research Directions from Psychology', ACM Computing Surveys, 57; Yang S et al. (2023), 'Reinforcement Learning Agents Playing Ticket to Ride—A Complex Imperfect Information Board Game With Delayed Rewards', IEEE Access, 11, pp. 60737-60757; Yang S et al. (2023), 'Automatic Recognition of Collective Emergent Behaviors Using Behavioral Metrics', IEEE Access, 11, pp. 89077-89092; Samarasinghe D et al. (2022), 'Grammar-based autonomous discovery of abstractions for evolution of complex multi-agent behaviours', Swarm and Evolutionary Computation, 73; Samarasinghe D, Barlow M, Lakshika E (2022), 'Flow-Based Reinforcement Learning', IEEE Access, 10, pp. 102247-102265; Debie E et al. (2021), 'Autonomous recommender system for reconnaissance tasks using a swarm of UAVs and asynchronous shepherding', Human-Intelligent Systems Integration, 3, pp. 175-186; Samarasinghe Widana Arachchige D et al. (2021), 'Exploiting Abstractions for Grammar-Based Learning of Complex Multi-Agent Behaviours', International Journal of Intelligent Systems, 36, pp. 6273-6311. His research interests extend to AI in international development and vulnerable states, AI and values/culture, swarm robotics, and human-swarm interaction.