| Robust distributed decision-making in robot swarms: Exploiting a third truth state M Crosscombe, J Lawry, S Hauert, M Homer 2017 IEEE/RSJ international conference on intelligent robots and systems …, 2017 | 24 | 2017 |
| A model of multi-agent consensus for vague and uncertain beliefs M Crosscombe, J Lawry Adaptive Behavior 24 (4), 249-260, 2016 | 16 | 2016 |
| The impact of network connectivity on collective learning M Crosscombe, J Lawry Distributed Autonomous Robotic Systems: 15th International Symposium, 82-94, 2022 | 15 | 2022 |
| Exploiting vagueness for multi-agent consensus M Crosscombe, J Lawry Multi-agent and Complex Systems, 67-78, 2017 | 13 | 2017 |
| Epistemic Sets Applied to Best-of-n Problems J Lawry, M Crosscombe, D Harvey Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 15th …, 2019 | 11 | 2019 |
| Evidence Propagation and Consensus Formation in Noisy Environments M Crosscombe, J Lawry, P Bartashevich International Conference on Scalable Uncertainty Management, 310-323, 2019 | 10 | 2019 |
| Evidence Propagation and Consensus Formation in Noisy Environments: Extended Abstract M Crosscombe, J Lawry International Conference on Autonomous Agents and Multiagent Systems, 1904-1906, 2019 | 10* | 2019 |
| Collective preference learning in the best-of-n problem: From best-of-n to ranking n M Crosscombe, J Lawry Swarm Intelligence 15 (1), 145-170, 2021 | 6 | 2021 |
| Imprecise fusion operators for collective learning Z Liu, M Crosscombe, J Lawry ALIFE 2021: The 2021 Conference on Artificial Life, 2021 | 4 | 2021 |
| Dual consensus measure for multi-perspective multi-criteria group decision making I Palomares, M Crosscombe, ZS Chen, J Lawry 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 4 | 2018 |
| The benefits of interaction constraints in distributed autonomous systems M Crosscombe, J Lawry International Symposium on Distributed Autonomous Robotic Systems, 14-27, 2022 | 2 | 2022 |
| Academic and industrial partnerships in the research and development of hybrid autonomous systems: challenges, tools and methods E Barden, M Crosscombe, K Galvin, C Harding, A Johnson, T Kent, ... International Conference on Modelling and Simulation for Autonomous Systems …, 2021 | 1 | 2021 |
| Distributed Possibilistic Learning in Multi-Agent Systems J Lawry, M Crosscombe, D Harvey The 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics, 2019 | 1* | 2019 |
| A model of multi-agent consensus for compound sentences M Crosscombe, J Lawry LFU-2017, 2017 | 1 | 2017 |
| Emergence of Differentiation of Deterministic/Stochastic Behavior in Ants’ Collectives N Maruyama, M Crosscombe, S Dobata, T Ikegami ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life …, 2023 | | 2023 |
| On the Existence of Information Bottlenecks in Living and Non-Living Systems M Crosscombe, H Sato arXiv preprint arXiv:2306.01806, 2023 | | 2023 |
| Imprecise Evidence in Social Learning Z Liu, M Crosscombe, J Lawry | | 2023 |
| Exploiting Vagueness for Multi-Agent Consensus M Crosscombe University of Bristol, 2018 | | 2018 |
Jonathan LawryProfessor of Artificial Intelligence, University of BristolVahvistettu sähköpostiosoite verkkotunnuksessa bris.ac.uk
