Cameron Foale

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 30

Top Topics

Multiobjective Evolutionary Algorithms

Reinforcement Learning

Top Venues

Neural Comput. Appl.

Publications

Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. CoRR (2024)
Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. AAMAS (2024)
Peter Vamplew, Cameron Foale, Richard Dazeley
Value function interference and greedy action selection in value-based multi-objective reinforcement learning. CoRR (2024)
Kewen Ding, Peter Vamplew, Cameron Foale, Richard Dazeley
An Empirical Investigation of Value-Based Multi-objective Reinforcement Learning for Stochastic Environments. CoRR (2024)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Human engagement providing evaluative and informative advice for interactive reinforcement learning. Neural Comput. Appl. 35 (25) (2023)
Adam Bignold, Francisco Cruz, Matthew E. Taylor, Tim Brys, Richard Dazeley, Peter Vamplew, Cameron Foale
A conceptual framework for externally-influenced agents: an assisted reinforcement learning review. J. Ambient Intell. Humaniz. Comput. 14 (4) (2023)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Persistent rule-based interactive reinforcement learning. Neural Comput. Appl. 35 (32) (2023)
Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Friedrik Hentz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
Scalar Reward is Not Enough. AAMAS (2023)
Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Auton. Agents Multi Agent Syst. 36 (2) (2022)
Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
Discrete-to-deep reinforcement learning methods. Neural Comput. Appl. 34 (3) (2022)
Peter Vamplew, Cameron Foale, Richard Dazeley
The impact of environmental stochasticity on value-based multiobjective reinforcement learning. Neural Comput. Appl. 34 (3) (2022)
Richard Dazeley, Peter Vamplew, Cameron Foale, Charlotte Young, Sunil Aryal, Francisco Cruz
Levels of explainable artificial intelligence for human-aligned conversational explanations. Artif. Intell. 299 (2021)
Richard Dazeley, Peter Vamplew, Cameron Foale, Charlotte Young, Sunil Aryal, Francisco Cruz
Levels of explainable artificial intelligence for human-aligned conversational explanations. CoRR (2021)
Peter Vamplew, Cameron Foale, Richard Dazeley, Adam Bignold
Potential-based multiobjective reinforcement learning approaches to low-impact agents for AI safety. Eng. Appl. Artif. Intell. 100 (2021)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Persistent Rule-based Interactive Reinforcement Learning. CoRR (2021)
Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021). CoRR (2021)
Goodger Nikolaj, Peter Vamplew, Cameron Foale, Richard Dazeley
Language Representations for Generalization in Reinforcement Learning. ACML (2021)
Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
Discrete-to-Deep Supervised Policy Learning. CoRR (2020)
Adam Bignold, Francisco Cruz, Matthew E. Taylor, Tim Brys, Richard Dazeley, Peter Vamplew, Cameron Foale
A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review. CoRR (2020)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning. CoRR (2020)
Peter Vamplew, Cameron Foale, Richard Dazeley
A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions. CoRR (2020)
Meena Santhanagopalan, Madhu Chetty, Cameron Foale, Britt Klein
Towards Machine Learning approach for Digital-Health intervention program. Aust. J. Intell. Inf. Process. Syst. 15 (3) (2019)
Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
An Empirical Study of Reward Structures for Actor-Critic Reinforcement Learning in Air Combat Manoeuvring Simulation. Australasian Conference on Artificial Intelligence (2019)
Meena Santhanagopalan, Madhu Chetty, Cameron Foale, Sunil Aryal, Britt Klein
Modeling neurocognitive reaction time with gamma distribution. ACSW (2018)
Alastair Lansley, Peter Vamplew, Cameron Foale, Philip Smith
SoniFight: Software to Provide Additional Sonification Cues to Video Games for Visually Impaired Players. Comput. Games J. 7 (2) (2018)
Peter Vamplew, Richard Dazeley, Cameron Foale, Tanveer A. Choudhury
Non-functional regression: A new challenge for neural networks. Neurocomputing 314 (2018)
Meena Santhanagopalan, Madhu Chetty, Cameron Foale, Sunil Aryal, Britt Klein
Relevance of Frequency of Heart-Rate Peaks as Indicator of 'Biological' Stress Level. ICONIP (7) (2018)
Peter Vamplew, Richard Dazeley, Cameron Foale, Sally Firmin, Jane Mummery
Human-aligned artificial intelligence is a multiobjective problem. Ethics Inf. Technol. 20 (1) (2018)
Peter Vamplew, Richard Dazeley, Cameron Foale
Softmax exploration strategies for multiobjective reinforcement learning. Neurocomputing 263 (2017)
Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale, Adam Berry, Tim Moore, Douglas C. Creighton
Steering approaches to Pareto-optimal multiobjective reinforcement learning. Neurocomputing 263 (2017)
Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale
Reinforcement Learning of Pareto-Optimal Multiobjective Policies Using Steering. Australasian Conference on Artificial Intelligence (2015)
Cameron Foale, Peter Vamplew
Portal-based sound propagation for first-person computer games. IE (2007)