Survey of intrusion detection systems: techniques, datasets and challenges A Khraisat, I Gondal, P Vamplew, J Kamruzzaman Cybersecurity 2 (1), 1-22, 2019 | 1451* | 2019 |
A Survey of Multi-Objective Sequential Decision-Making DM Roijers, P Vamplew, S Whiteson, R Dazeley Journal of Artificial Intelligence Research 48, 67-113, 2013 | 726 | 2013 |
Empirical evaluation methods for multiobjective reinforcement learning algorithms P Vamplew, R Dazeley, A Berry, R Issabekov, E Dekker Machine learning, 1-30, 2011 | 363 | 2011 |
A practical guide to multi-objective reinforcement learning and planning CF Hayes, R Rădulescu, E Bargiacchi, J Källström, M Macfarlane, ... Autonomous Agents and Multi-Agent Systems 36 (1), 1-59, 2022 | 262 | 2022 |
A novel Ensemble of Hybrid Intrusion Detection System for Detecting Internet of Things Attacks A Khraisat, I Gondal, P Vamplew, J Kamruzzaman, A Alazab Electronics 8 (11), 1210, 2019 | 218 | 2019 |
Hybrid Intrusion Detection System Based on the Stacking Ensemble of C5 Decision Tree Classifier and One Class Support Vector Machine A Khraisat, I Gondal, P Vamplew, J Kamruzzaman, A Alazab Electronics 9 (1), 173, 2020 | 179 | 2020 |
On the Limitations of Scalarisation for Multi-objective Reinforcement Learning of Pareto Fronts P Vamplew, J Yearwood, R Dazeley, A Berry AI 2008: Advances in Artificial Intelligence, 372-378, 2008 | 154 | 2008 |
Human-aligned artificial intelligence is a multiobjective problem P Vamplew, R Dazeley, C Foale, S Firmin, J Mummery Ethics and Information Technology 20 (1), 27-40, 2018 | 145 | 2018 |
A multi-objective deep reinforcement learning framework TT Nguyen, ND Nguyen, P Vamplew, S Nahavandi, R Dazeley, CP Lim Engineering Applications of Artificial Intelligence 96, 103915, 2020 | 127 | 2020 |
Recognition of sign language gestures using neural networks P Vamplew, A Adams Australian Journal of Intelligent Information Processing Systems 5 (2), 94-102, 1998 | 127 | 1998 |
Levels of Explainable Artificial Intelligence for Human-Aligned Conversational Explanations R Dazeley, P Vamplew, C Foale, C Young, S Aryal, F Cruz Artificial Intelligence, 103525, 2021 | 105 | 2021 |
An Anomaly Intrusion Detection System Using C5 Decision Tree Classifier A Khraisat, I Gondal, P Vamplew Pacific-Asia Conference on Knowledge Discovery and Data Mining, 149-155, 2018 | 87 | 2018 |
Constructing stochastic mixture policies for episodic multiobjective reinforcement learning tasks P Vamplew, R Dazeley, E Barker, A Kelarev AI 2009: Advances in Artificial Intelligence, 340-349, 2009 | 62 | 2009 |
Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021) P Vamplew, BJ Smith, J Källström, G Ramos, R Rădulescu, DM Roijers, ... Autonomous Agents and Multi-Agent Systems 36 (2), 1-19, 2022 | 60 | 2022 |
A taxonomy of griefer type by motivation in massively multiplayer online role-playing games L Achterbosch, C Miller, P Vamplew Behaviour & Information Technology 36 (8), 846-860, 2017 | 60 | 2017 |
Softmax exploration strategies for multiobjective reinforcement learning P Vamplew, R Dazeley, C Foale Neurocomputing 263, 74-86, 2017 | 59 | 2017 |
An anti-plagiarism editor for software development courses P Vamplew, J Dermoudy Proceedings of the 7th Australasian conference on Computing education-Volume …, 2005 | 55 | 2005 |
Explainable reinforcement learning for broad-xai: a conceptual framework and survey R Dazeley, P Vamplew, F Cruz Neural Computing and Applications 35 (23), 16893-16916, 2023 | 49 | 2023 |
Applying clustering and ensemble clustering approaches to phishing profiling J Yearwood, D Webb, L Ma, P Vamplew, B Ofoghi, A Kelarev Eighth Australasian Data Mining Conference, AusDM, 25-34, 2009 | 49 | 2009 |
A Comparative Study of Various Data Mining Techniques as applied to the Modeling of Landslide Susceptibility on the Bellarine Peninsula, Victoria, Australia AS Miner, P Vamplew, DJ Windle, P Flentje, P Warner | 46 | 2010 |