Peter Vamplew
Peter Vamplew
Professor, Information Technology, Federation University Australia
Verifierad e-postadress på federation.edu.au - Startsida
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Citeras av
Survey of intrusion detection systems: techniques, datasets and challenges
A Khraisat, I Gondal, P Vamplew, J Kamruzzaman
Cybersecurity 2 (1), 1-22, 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
Empirical evaluation methods for multiobjective reinforcement learning algorithms
P Vamplew, R Dazeley, A Berry, R Issabekov, E Dekker
Machine learning, 1-30, 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
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
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
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
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
Recognition of sign language gestures using neural networks
P Vamplew, A Adams
Australian Journal of Intelligent Information Processing Systems 5 (2), 94-102, 1998
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
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
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
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
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
Softmax exploration strategies for multiobjective reinforcement learning
P Vamplew, R Dazeley, C Foale
Neurocomputing 263, 74-86, 2017
An anti-plagiarism editor for software development courses
P Vamplew, J Dermoudy
Proceedings of the 7th Australasian conference on Computing education-Volume …, 2005
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
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
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
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
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Artiklar 1–20