| Exploiting subgraph structure in multi-robot path planning MRK Ryan Journal of Artificial Intelligence Research 31, 497-542, 2008 | 248 | 2008 |
| Graph Decomposition for Efficient Multi-Robot Path Planning. M Ryan IJCAI, 2003-2008, 2007 | 93 | 2007 |
| Using abstract models of behaviours to automatically generate reinforcement learning hierarchies MRK Ryan Proceedings of the Nineteenth International Conference on Machine Learning …, 2002 | 75 | 2002 |
| Papers, Please and the systemic approach to engaging ethical expertise in videogames DS Paul Formosa, Malcolm Ryan Ethics and Information Technology, 2016 | 71 | 2016 |
| Constraint-based multi-robot path planning M Ryan 2010 IEEE International Conference on Robotics and Automation, 922-928, 2010 | 67 | 2010 |
| RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning. MRK Ryan, MD Pendrith ICML, 481-487, 1998 | 56 | 1998 |
| Making moral machines: why we need artificial moral agents P Formosa, M Ryan AI & society 36 (3), 839-851, 2021 | 45 | 2021 |
| Development of a novel approach to the assessment of eye–hand coordination K Lee, BM Junghans, M Ryan, S Khuu, CM Suttle Journal of neuroscience methods 228, 50-56, 2014 | 43 | 2014 |
| Morality play: a model for developing games of moral expertise D Staines, P Formosa, M Ryan Games and Culture 14 (4), 410-429, 2019 | 38 | 2019 |
| Hierarchical reinforcement learning: A hybrid approach MRK Ryan UNSW Sydney, 2002 | 34 | 2002 |
| Learning to fly: An application of hierarchical reinforcement learning MRK Ryan, M Reid Proceedings of the Seventeenth International Conference on Machine Learning …, 2000 | 28 | 2000 |
| Multi-robot path planning with sub-graphs MRK Ryan Proceedings of the 19th Australasian Conference on Robotics and Automation …, 2006 | 27 | 2006 |
| Normative values for a tablet computer-based application to assess chromatic contrast sensitivity L Bodduluri, MY Boon, M Ryan, SJ Dain Behavior Research Methods, 2017 | 20 | 2017 |
| Actual return reinforcement learning versus Temporal Differences: Some theoretical and experimental results MD Pendrith, MRK Ryan ICML, 373-381, 1996 | 19 | 1996 |
| Using ILP to improve planning in hierarchical reinforcement learning M Reid, M Ryan International Conference on Inductive Logic Programming, 174-190, 2000 | 18 | 2000 |
| Estimator variance in reinforcement learning: Theoretical problems and practical solutions MD Pendrith, MRK Ryan, CC Sammut University of New South Wales, School of Computer Science and Engineering, 1997 | 18 | 1997 |
| Four lenses for designing morally engaging games M Ryan, D Staines, P Formosa | 17 | 2016 |
| Deep Learning Games through the Lens of the Toy M Ryan, B Costello, A Stapleton Meaningful Play 2012, 2012 | 17 | 2012 |
| Focus, Sensitivity, Judgement, Action M Ryan, D Staines, P Formosa Transactions of DiGRA 3 (2), 143-173, 2017 | 16* | 2017 |
| Treatment and compliance with virtual reality and anaglyph‐based training programs for convergence insufficiency MY Boon, LJ Asper, P Chik, P Alagiah, M Ryan Clinical and Experimental Optometry 103 (6), 870-876, 2020 | 15 | 2020 |
Dan StainesTorrens UniversityVerified email at danstaines.com
