Cameron Foale

601 total citations
22 papers, 360 citations indexed

About

Cameron Foale is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Control and Systems Engineering. According to data from OpenAlex, Cameron Foale has authored 22 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 4 papers in Cognitive Neuroscience and 2 papers in Control and Systems Engineering. Recurrent topics in Cameron Foale's work include Reinforcement Learning in Robotics (8 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Explainable Artificial Intelligence (XAI) (2 papers). Cameron Foale is often cited by papers focused on Reinforcement Learning in Robotics (8 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Explainable Artificial Intelligence (XAI) (2 papers). Cameron Foale collaborates with scholars based in Australia, United States and United Kingdom. Cameron Foale's co-authors include Peter Vamplew, Richard Dazeley, Francisco Cruz, Jane Mummery, Sally Firmin, Charlotte Young, Sunil Aryal, Douglas R. Hamilton, Ashot E. Sargsyan and David S. Martin and has published in prestigious journals such as Artificial Intelligence, Neurocomputing and Neural Computing and Applications.

In The Last Decade

Cameron Foale

22 papers receiving 338 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Cameron Foale 165 63 39 29 27 22 360
Ángel Fernández-Leal 157 1.0× 34 0.5× 10 0.3× 20 0.7× 20 0.7× 9 411
Sayash Kapoor 153 0.9× 57 0.9× 27 0.7× 30 1.0× 6 0.2× 15 435
Felix Lindner 110 0.7× 82 1.3× 19 0.5× 41 1.4× 28 1.0× 40 434
Nathan Bartley 170 1.0× 6 0.1× 28 0.7× 12 0.4× 17 0.6× 6 396
Yichao Zhou 310 1.9× 19 0.3× 11 0.3× 15 0.5× 6 0.2× 29 571
José Bobes-Bascarán 155 0.9× 36 0.6× 10 0.3× 14 0.5× 20 0.7× 7 383
Meike Nauta 396 2.4× 21 0.3× 13 0.3× 24 0.8× 32 1.2× 13 620
Carmen Peláez-Moreno 286 1.7× 6 0.1× 118 3.0× 26 0.9× 17 0.6× 62 563
Christophe Marsala 173 1.0× 4 0.1× 65 1.7× 20 0.7× 19 0.7× 36 290

Countries citing papers authored by Cameron Foale

Since Specialization
Citations

This map shows the geographic impact of Cameron Foale's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cameron Foale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cameron Foale more than expected).

Fields of papers citing papers by Cameron Foale

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cameron Foale. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cameron Foale. The network helps show where Cameron Foale may publish in the future.

Co-authorship network of co-authors of Cameron Foale

This figure shows the co-authorship network connecting the top 25 collaborators of Cameron Foale. A scholar is included among the top collaborators of Cameron Foale based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cameron Foale. Cameron Foale is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gkantonas, Savvas, et al.. (2023). Simulation of the December 2021 Marshall fire with a hybrid stochastic Lagrangian-cellular automata model. Fire Safety Journal. 138. 103795–103795. 5 indexed citations
2.
Goodger, N.M., Peter Vamplew, Cameron Foale, & Richard Dazeley. (2023). A NetHack Learning Environment Language Wrapper for Autonomous Agents. Journal of Open Research Software. 11. 1 indexed citations
3.
Vamplew, Peter, Benjamin J. Smith, Johan Källström, et al.. (2022). Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Autonomous Agents and Multi-Agent Systems. 36(2). 18 indexed citations
4.
Cruz, Francisco, et al.. (2022). Human engagement providing evaluative and informative advice for interactive reinforcement learning. Neural Computing and Applications. 35(25). 18215–18230. 12 indexed citations
5.
Chand, Savin S., et al.. (2022). Statistical Calibration of Long-Term Reanalysis Data for Australian Fire Weather Conditions. Journal of Applied Meteorology and Climatology. 61(6). 729–758. 3 indexed citations
6.
Cruz, Francisco, et al.. (2021). An Evaluation Methodology for Interactive Reinforcement Learning with Simulated Users. Biomimetics. 6(1). 13–13. 8 indexed citations
7.
Dazeley, Richard, Peter Vamplew, Cameron Foale, et al.. (2021). Levels of explainable artificial intelligence for human-aligned conversational explanations. Artificial Intelligence. 299. 103525–103525. 69 indexed citations
8.
Vamplew, Peter, et al.. (2021). Discrete-to-deep reinforcement learning methods. Neural Computing and Applications. 34(3). 1713–1733. 1 indexed citations
9.
Vamplew, Peter, Cameron Foale, & Richard Dazeley. (2021). The impact of environmental stochasticity on value-based multiobjective reinforcement learning. Neural Computing and Applications. 34(3). 1783–1799. 12 indexed citations
10.
Vamplew, Peter, Richard Dazeley, Cameron Foale, & Tanveer Choudhury. (2018). Non-functional regression: A new challenge for neural networks. Neurocomputing. 314. 326–335. 1 indexed citations
11.
Chetty, Madhu, et al.. (2018). Modeling neurocognitive reaction time with gamma distribution. Proceedings of the Australasian Computer Science Week Multiconference. 1–10. 3 indexed citations
12.
Vamplew, Peter, Richard Dazeley, & Cameron Foale. (2017). Softmax exploration strategies for multiobjective reinforcement learning. Neurocomputing. 263. 74–86. 39 indexed citations
13.
Vamplew, Peter, et al.. (2017). Steering approaches to Pareto-optimal multiobjective reinforcement learning. Neurocomputing. 263. 26–38. 22 indexed citations
14.
Vamplew, Peter, Richard Dazeley, Cameron Foale, Sally Firmin, & Jane Mummery. (2017). Human-aligned artificial intelligence is a multiobjective problem. Ethics and Information Technology. 20(1). 27–40. 67 indexed citations
15.
Vamplew, Peter, et al.. (2016). Caliko: An Inverse Kinematics Software Library Implementation of the FABRIK Algorithm. Journal of Open Research Software. 4(1). 36–36. 2 indexed citations
16.
Lu, Peter J., Hidekazu Oki, Gregory Chamitoff, et al.. (2009). Orders-of-magnitude performance increases in GPU-accelerated correlation of images from the International Space Station. Journal of Real-Time Image Processing. 5(3). 179–193. 17 indexed citations
17.
Foale, Cameron & Peter Vamplew. (2007). Portal-based sound propagation for first-person computer games. 9. 4 indexed citations
18.
Foale, Cameron, Ashot E. Sargsyan, Douglas R. Hamilton, et al.. (2005). Diagnostic instrumentation aboard ISS: just-in-time training for non-physician crewmembers.. PubMed. 76(6). 594–8. 56 indexed citations
19.
Foale, Cameron, Ashot E. Sargsyan, Douglas R. Hamilton, et al.. (2004). Accelerated Training at Mach 20: A Brief Communication Submitted from the International Space Station. NASA Technical Reports Server (NASA). 1 indexed citations
20.
Foale, Cameron, et al.. (1991). Man Overboard Rescue. SIMULATION. 57(1). 39–47. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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