| Fake reviews detection: A survey R Mohawesh, S Xu, SN Tran, R Ollington, M Springer, Y Jararweh, ... Ieee Access 9, 65771-65802, 2021 | 158 | 2021 |
| A computer simulation of community pharmacy practice for educational use I Bindoff, T Ling, L Bereznicki, J Westbury, L Chalmers, G Peterson, ... American journal of pharmaceutical education 78 (9), 168, 2014 | 60 | 2014 |
| Analysis of concept drift in fake reviews detection R Mohawesh, S Tran, R Ollington, S Xu Expert Systems with Applications 169, 114318, 2021 | 59 | 2021 |
| Incorporating expert advice into reinforcement learning using constructive neural networks R Ollington, P Vamplew, J Swanson Constructive Neural Networks, 207-224, 2009 | 43 | 2009 |
| Concurrent Q‐learning: Reinforcement learning for dynamic goals and environments RB Ollington, PW Vamplew International journal of intelligent systems 20 (10), 1037-1052, 2005 | 19 | 2005 |
| Convolutional Neural Networks for individual identification in the Southern Rock Lobster supply chain SA Vo, J Scanlan, P Turner, R Ollington Food Control 118, 107419, 2020 | 18 | 2020 |
| Global versus local constructive function approximation for on-line reinforcement learning P Vamplew, R Ollington Australasian Joint Conference on Artificial Intelligence, 113-122, 2005 | 18 | 2005 |
| Onboard assessment of XRF spectra using genetic algorithms for decision making on an autonomous underwater vehicle J Breen, P De Souza, GP Timms, R Ollington Nuclear Instruments and Methods in Physics Research Section B: Beam …, 2011 | 11 | 2011 |
| Effect of constraints on evolving behavior trees for game AI P McClarron, R Ollington, I Lewis International Conference on Computer Games, Multimedia & Allied Technology …, 2016 | 10 | 2016 |
| On-line reinforcement learning using cascade constructive neural networks P Vamplew, R Ollington International Conference on Knowledge-Based and Intelligent Information and …, 2005 | 9 | 2005 |
| Learning place cells from sonar data R Ollington, P Vamplew International Conference on Artificial Intelligence in Science and …, 2004 | 8 | 2004 |
| Predictive ACT-R (PACT-R): using a physics engine and simulation for physical prediction in a cognitive architecture D Pentecost, C Sennersten, R Ollington, CA Lindley, B Kang University Of Tasmania, 2016 | 7 | 2016 |
| Analysis of heavy metals in marine sediment using a portable X-ray fluorescence spectrometer onboard an Autonomous Underwater Vehicle J Breen, P de Souza, G Timms, J McCulloch, R Ollington 2012 Oceans-Yeosu, 1-5, 2012 | 5 | 2012 |
| Concurrent q-learning for autonomous mapping and navigation R Ollington, P Vamplew University Of Tasmania, 2003 | 5 | 2003 |
| Adaptive response function neurons R Ollington, P Vamplew University Of Tasmania, 2003 | 5 | 2003 |
| Using a physics engine in ACT-R to aid decision making D Pentecost¹, C Sennersten, R Ollington¹, CA Lindley, B Kang¹ | 4 | 2016 |
| Localisation and navigation: applying biological principles in mobile robotics R Ollington University Of Tasmania, 2007 | 2 | 2007 |
| Accurate image-space environment reflections in real-time A Grace, R Ollington, I Lewis International Conference on Computer Games, Multimedia & Allied Technology …, 2016 | 1 | 2016 |
| Hydrologic model parameter optimisation WJ Cohen, R Ollington, FLN Ling University Of Tasmania, 2013 | 1 | 2013 |
| Adaptive behaviour for an Autonomous Underwater Vehicle to perform chemical mappings J Breen, PA de Souza, GP Timms, R Ollington OCEANS'10 IEEE SYDNEY, 1-6, 2010 | 1 | 2010 |
Peter VamplewProfessor, Information Technology, Federation University AustraliaVerified email at federation.edu.au
