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e-mail: j.borg@aston.ac.uk
twitter: @JamesMBorg
Aston homepage: james-borg
ORCID:
James_Borg
Scholar:
James Borg
Bio
Bio
I am Lecturer in Computer Science in the Department on Applied AI and Robotics in the School of Computer Science and Digital Technologies, Aston University, UK, a Management Committee for the Aston Centre for AI Research and Applications (ACAIRA), and a member of the ALICE research group. My research interests can be broadly described as Social Learning, Cultural Evolution and Adaptive Change in Artificial Evolutionary Systems. More details about my research can be found on my Research Interests and Publications pages.
Current Research Projects:
Artificial General Adaptiveness
"Open-Ended (Cumulative) Cultural Evolution"
"Fair mechanisms for energy exchange in community energy systems"
Computational Intelligence and Evolutionary Systems techniques for Arbovirus modelling
I am originally from Birmingham, and am proudly half Maltese. Before moving to Aston University in January 2022 I was Lecturer in Evolutionary Systems at Keele University, UK (joining in 2009 to begin my PhD and Teaching Fellowship). Before undertaking a PhD I studied for a BSc in Artificial Intelligence and Computer Science and a MSc in Advance Computer Science at the University of Birmingham, UK.
In my spare time I am a keen Aston Villa supporter; regularly injured football player; music enthusiast; out of practice guitarist; Science Fiction fan, part time gamer, part time politico, part time meme stock enthusiast; and full time Dad and partner.
Injury Status: My knees are totally shot - time to start playing Golf!
Currently Listening: How to be a Footballer - Peter Crouch (Audiobook), History of the Anglo Saxons (Podcast), Zeal and Ardor (Music)
Currently Reading: How to be a Liberal - Ian Dunt (non-fiction), Sharpe's Triumph - Bernard Cornwell (fiction)
Currently Playing: Civilization VI and Crusader Kings 3
Investments Status: Getting in early on the Robotics boom!
My Reading List
My Reading List
I have built up a bad habit of buying books and bookmarking paper, so I have decided to list everything I have on my stack to read here. Hopefully this will shame me into making some headway in to these (or at least stop buying books and bookmarking papers). If you are interested, feel free to expand the sections below.
Books
(Fiction)
Books
(Fiction)
Once Upon a Time in the North by Philip Pullman
The Wandering Earth by Cixin Liu
The Wheel of Time - The Eye of the World by Robert Jordan
The Wheel of Time - The Great Hunt by Robert Jordan
The Wheel of Time - The Dragon Reborn by Robert Jordan
Sharpe's Tiger by Bernard Cornwell
Sharpe's Triumph by Bernard Cornwell
Unfinished Tales of Numenor and Middle Earth by J.R.R. Tolkien
The Salmon of Doubt by Douglas Adams
The Book of Dust - Volume Two: The Secret Commonwealth by Philip Pullman
Books
(Non-Fiction)
Books
(Non-Fiction)
How to be a Liberal by Ian Dunt
A Brief History of Everyone Who Ever Lived by Adam Rutherford
The Book of Humans by Adam Rutherford
How to Argue with a Racist by Adam Rutherford
The Complete Guide to Absolutely Everything by Adam Rutherford and Hannah Fry
Wales - History of a Nation by David Ross
A Time for Princes - The Welsh Leaders who Forged a Nation 800-1282 by Michael Senior
The Norman Conquest by Marc Morris
The Storm Before the Storm - The Beginning of the End of the Roman Republic by Mike Duncan
Books
(Research)
Books
(Research)
Life edited by William Brown and Andrew Fabian
Papers
(Research)
Papers
(Research)
Thompson, B., Van Opheusden, B., Sumers, T., & Griffiths, T. L. (2022). Complex cognitive algorithms preserved by selective social learning in experimental populations. Science, 376(6588), 95-98. https://doi.org/10.1126/science.abn0915
Miconi, T. (2022, July). Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1971-1978). https://doi.org/10.1145/3520304.3533981
Schmidgall, S., Achterberg, J., Miconi, T., Kirsch, L., Ziaei, R., Hajiseyedrazi, S., & Eshraghian, J. (2023). Brain-inspired learning in artificial neural networks: a review. arXiv preprint arXiv:2305.11252. https://doi.org/10.48550/arXiv.2305.11252
Watson, R., & Levin, M. (2023). The collective intelligence of evolution and development. Collective Intelligence, 2(2). https://doi.org/10.1177/26339137231168355
Jops, K., & O’Dwyer, J. P. (2023). Life history complementarity and the maintenance of biodiversity. Nature, 1-6. https://doi.org/10.1038/s41586-023-06154-w
Turner, M. A., Moya, C., Smaldino, P. E., & Jones, J. H. (2023). The form of uncertainty affects selection for social learning. Evolutionary Human Sciences, 5, e20. https://doi.org/10.1017/ehs.2023.11
Smaldino, P. E., Moser, C., Velilla, A. P., & Werling, M. (2022). Maintaining transient diversity is a general principle for improving collective problem solving. Perspectives on Psychological Science. https://osf.io/ykrv5/download
Boroomand, A., & Smaldino, P. E. (2023). Superiority Bias and Communication Noise Can Enhance Collective Problem Solving. https://osf.io/gp8mj/download
Reeves, J. S., Proffitt, T., Almeida-Warren, K., & Luncz, L. V. (2023). Modeling Oldowan tool transport from a primate perspective. Journal of Human Evolution, 181, 103399. https://doi.org/10.1016/j.jhevol.2023.103399
Bianchi, F., & Squazzoni, F. (2015). Agent‐based models in sociology. Wiley Interdisciplinary Reviews: Computational Statistics, 7(4), 284-306. https://doi.org/10.1002/wics.1356
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