AI Strategy and Concepts Bibliography

Welcome to the AI Strategy and Concepts Bibliography site. The site uses the Wikindx bibliography tool to offer a variety of search options across sources we've targeted for tracking in several related domains of research shaping and impacting artificial intelligence (AI) and its influence on strategy and concepts: cognitive science, neuroscience, complexity science, computer science, military science, machine learning, deep learning, neural nets, robotics, advanced wargaming, augmented cognition and decisionmaking, quantum computing, adaptive networks, informatics, analytics, data sciences, to name a few areas that are increasingly converging in advanced theory, practices, and applications. The latest 20 additions to the bibliography are displayed below but hundreds of sources are searchable. We attempt to emphasize current sources along with foundational references underpinning major areas of research impacting AI. This site also supports neural nets used by AI engines employed in our simulations. If you wish to contribute to the bibliography please register under the Wikindx menu option. You can also return to the AI Strategy and Concepts Hub from the Wikindx menu option. 

Recent additions or edits

Lecun, Y. (2022). A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27. Open Review, 62,
Last edited by: SijanLibrarian 2023-01-18 12:42:29 Pop. 0%
Bengio, Y., Lecun, Y., & Hinton, G. (2021). Deep learning for ai. Communications of the ACM, 64(7), 58–65.
Last edited by: SijanLibrarian 2023-01-18 12:34:59 Pop. 0%
Still, S., & Precup, D. (2012). An information-theoretic approach to curiosity-driven reinforcement learning. Theory in Biosciences, 131(3), 139–148.
Last edited by: SijanLibrarian 2023-01-18 06:35:35 Pop. 0%
Lempert, R. J. (2019). Robust decision making (rdm). In Decision making under deep uncertainty (pp. 23–51).Springer, Cham.
Last edited by: SijanLibrarian 2023-01-17 14:27:14 Pop. 0%
Dubey, R., & Griffiths, T. L. (2020). Understanding exploration in humans and machines by formalizing the function of curiosity. Current Opinion in Behavioral Sciences, 35, 118–124.
Last edited by: SijanLibrarian 2023-01-03 10:50:51 Pop. 0%
Friston, K. J., Lin, M., Frith, C. D., Pezzulo, G., Hobson, J. A., & Ondobaka, S. (2017). Active inference, curiosity and insight. Neural computation, 29(10), 2633–2683.
Last edited by: SijanLibrarian 2023-01-03 10:41:07 Pop. 0%
Gottlieb, J., & Oudeyer, P.-Y. (2018). Towards a neuroscience of active sampling and curiosity. Nature Reviews Neuroscience, 19(12), 758–770.
Last edited by: SijanLibrarian 2023-01-03 10:24:22 Pop. 0%
Oudeyer, P.-Y. (2018). Computational theories of curiosity-driven learning. arXiv preprint arXiv:1802.10546,
Last edited by: SijanLibrarian 2023-01-03 10:17:54 Pop. 0%
Sun, C., Qian, H., & Miao, C. (2022). From psychological curiosity to artificial curiosity: Curiosity-driven learning in artificial intelligence tasks. arXiv preprint arXiv:2201.08300,
Last edited by: SijanLibrarian 2023-01-03 10:12:27 Pop. 0%
Mohakud, R., & Dash, R. (2022). Designing a grey wolf optimization based hyper-parameter optimized convolutional neural network classifier for skin cancer detection. Journal of King Saud University-Computer and Information Sciences, 34(8), 6280–6291.
Last edited by: SijanLibrarian 2022-12-14 16:50:01 Pop. 0%
Boden, M. A. (2014). Creativity and artificial intelligence: A contradiction in terms. The philosophy of creativity: New essays, 224–246.
Last edited by: SijanLibrarian 2022-12-12 15:42:04 Pop. 0%
Heisenberg, W. (1958). The representation of nature in contemporary physics. Daedalus, 87(3), 95–108.
Last edited by: SijanLibrarian 2022-12-12 14:06:53 Pop. 0%
Klein, G., Phillips, J. K., Rall, E. L., & Peluso, D. A. (2007). A data--frame theory of sensemaking. In Expertise out of context (pp. 118–160).Psychology Press.
Last edited by: SijanLibrarian 2022-12-12 12:45:41 Pop. 0%
Tovstiga, G. (2015). Strategy in practice: A practitioner's guide to strategic thinking. John Wiley & Sons.
Last edited by: SijanLibrarian 2022-12-12 11:16:22 Pop. 0%
Halina, M. (2020). Insightful artificial intelligence. Mind & Language, 36(2), 315–329.
Last edited by: SijanLibrarian 2022-12-12 10:35:41 Pop. 0%
Li, B., Pei, Y., Wu, H., & Shen, B. (2015). Heuristics to allocate high-performance cloudlets for computation offloading in mobile ad hoc clouds. The Journal of Supercomputing, 71(8), 3009–3036.
Last edited by: SijanLibrarian 2022-12-12 09:50:32 Pop. 0%
Rajovic, N., Carpenter, P. M., Gelado, I., Puzovic, N., Ramirez, A., & Valero, M. 2013, Supercomputing with commodity cpus: Are mobile socs ready for hpc? Paper presented at Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis.
Last edited by: SijanLibrarian 2022-12-12 09:27:58 Pop. 0%
Hill, M., & Reddi, V. J. 2019, Gables: A roofline model for mobile socs. Paper presented at 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA).
Last edited by: SijanLibrarian 2022-12-12 09:09:59 Pop. 0%
Wei, J., Chen, M., Wang, L., Ren, P., Lei, Y., & Qu, Y., et al. (2022). Status, challenges and trends of data-intensive supercomputing. CCF Transactions on High Performance Computing, 1–20.
Last edited by: SijanLibrarian 2022-12-11 13:51:35 Pop. 0%
Huerta, E. A., Khan, A., Davis, E., Bushell, C., Gropp, W. D., & Katz, D. S., et al. (2020). Convergence of artificial intelligence and high performance computing on nsf-supported cyberinfrastructure. Journal of Big Data, 7(1), 1–12.
Last edited by: SijanLibrarian 2022-12-11 13:45:13 Pop. 0%
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