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Cameron Foale
Cameron Foale
Verified email at federation.edu.au
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Cited by
Cited by
Year
Human-aligned artificial intelligence is a multiobjective problem
P Vamplew, R Dazeley, C Foale, S Firmin, J Mummery
Ethics and Information Technology 20, 27-40, 2018
1322018
Levels of explainable artificial intelligence for human-aligned conversational explanations
R Dazeley, P Vamplew, C Foale, C Young, S Aryal, F Cruz
Artificial Intelligence 299, 103525, 2021
892021
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), 41, 2022
572022
Softmax exploration strategies for multiobjective reinforcement learning
P Vamplew, R Dazeley, C Foale
Neurocomputing 263, 74-86, 2017
542017
Steering approaches to Pareto-optimal multiobjective reinforcement learning
P Vamplew, R Issabekov, R Dazeley, C Foale, A Berry, T Moore, ...
Neurocomputing 263, 26-38, 2017
342017
A conceptual framework for externally-influenced agents: An assisted reinforcement learning review
A Bignold, F Cruz, ME Taylor, T Brys, R Dazeley, P Vamplew, C Foale
Journal of Ambient Intelligence and Humanized Computing 14 (4), 3621-3644, 2023
302023
The impact of environmental stochasticity on value-based multiobjective reinforcement learning
P Vamplew, C Foale, R Dazeley
Neural Computing and Applications, 1-17, 2022
222022
Persistent rule-based interactive reinforcement learning
A Bignold, F Cruz, R Dazeley, P Vamplew, C Foale
Neural Computing and Applications, 1-18, 2021
222021
Human engagement providing evaluative and informative advice for interactive reinforcement learning
A Bignold, F Cruz, R Dazeley, P Vamplew, C Foale
Neural Computing and Applications 35 (25), 18215-18230, 2023
202023
Potential-based multiobjective reinforcement learning approaches to low-impact agents for AI safety
P Vamplew, C Foale, R Dazeley, A Bignold
Engineering Applications of Artificial Intelligence 100, 104186, 2021
202021
An empirical study of reward structures for actor-critic reinforcement learning in air combat manoeuvring simulation
B Kurniawan, P Vamplew, M Papasimeon, R Dazeley, C Foale
Australasian Joint Conference on Artificial Intelligence, 54-65, 2019
182019
An evaluation methodology for interactive reinforcement learning with simulated users
A Bignold, F Cruz, R Dazeley, P Vamplew, C Foale
Biomimetics 6 (1), 13, 2021
172021
Portal-based sound propagation for first-person computer games
C Foale, P Vamplew
Proceedings of the 4th Australasian conference on Interactive entertainment, 1-8, 2007
162007
Caliko: An inverse kinematics software library implementation of the FABRIK algorithm
A Lansley, P Vamplew, P Smith, C Foale
Journal of Open Research Software 4 (1), e36-e36, 2016
112016
Reinforcement learning of Pareto-optimal multiobjective policies using steering
P Vamplew, R Issabekov, R Dazeley, C Foale
AI 2015: Advances in Artificial Intelligence: 28th Australasian Joint …, 2015
82015
SoniFight: Software to provide additional sonification cues to video games for visually impaired players
A Lansley, P Vamplew, C Foale, P Smith
The Computer Games Journal 7, 115-130, 2018
62018
Modeling neurocognitive reaction time with gamma distribution
M Santhanagopalan, M Chetty, C Foale, S Aryal, B Klein
Proceedings of the Australasian Computer Science Week Multiconference, 1-10, 2018
52018
A demonstration of issues with value-based multiobjective reinforcement learning under stochastic state transitions
P Vamplew, C Foale, R Dazeley
arXiv preprint arXiv:2004.06277, 2020
32020
Rule-based interactive assisted reinforcement learning
A Bignold, P Vamplew, R Dazeley, C Foale
Ph. D. Thesis, 2019
32019
Statistical calibration of long-term reanalysis data for Australian fire weather conditions
S Biswas, SS Chand, AJ Dowdy, W Wright, C Foale, X Zhao, A Deo
Journal of Applied Meteorology and Climatology 61 (6), 729-758, 2022
22022
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