Rate My Professor Jonathan Lawry

Professor Jonathan Lawry holds the position of Professor of Artificial Intelligence in the School of Engineering Mathematics and Technology at the University of Bristol. He earned a B.Sc. from the Council for National Academic Awards (CNAA) and a Ph.D. from the University of Manchester. As Head of the Intelligent Systems Laboratory, he is also affiliated with the Cabot Institute for the Environment. His research specializations encompass artificial intelligence, approximate reasoning, uncertainty modelling, probabilistic approaches to vagueness, imprecise probability, language games, consensus modelling, social learning, distributed decision making, swarm robotics, distributed AI, robot swarms, and resistance to misinformation. Lawry serves as Principal Investigator on the project 'Information Theory for Interactive Distributed AI' from 2024 to 2029 and 'Opinion Pooling in Robot Swarms' in 2016. He is Co-Investigator on 'T-B PHASE: Prosperity Partnership with Thales' from 2017 to 2023.

Lawry authored the book 'Modelling and Reasoning with Vague Concepts' published by Springer in 2006. His prominent publications include 'Hierarchical Conceptual Spaces for Concept Combination' with M. Lewis in Artificial Intelligence (2016), 'Probability Pooling for Dependent Agents in Collective Learning' in Artificial Intelligence (2020), 'A Framework for Linguistic Modelling' in Artificial Intelligence (2004), 'Imprecise Evidence in Social Learning' with Z. Liu and M. Crosscombe in Swarm Intelligence (2024), 'Incorporating Memory into Bounded Confidence Models of Probabilistic Social Learning' in Collective Intelligence (2026), 'Negative Updating Applied to the Best-of-n Problem with Noisy Qualities' with C. Lee and A. F. T. Winfield in Swarm Intelligence (2021), 'Combining Opinion Pooling and Evidential Updating for Multi-Agent Consensus' with C. Lee and A. Winfield at IJCAI (2018), 'Vagueness and Aggregation in Multiple Sender Channels' with O. James in Erkenntnis (2017), 'Probability, Fuzziness and Borderline Cases' in International Journal of Approximate Reasoning (2014), and 'Language Games with Vague Categories and Negations' with H. Eyre in Adaptive Behaviour (2014). These works have advanced understanding in collective intelligence, probabilistic social learning, and vague concept modelling within AI.