F. Aki, R. Ikeda, T. Saito, C. Regan, M. Oka “LLM-POET: Evolving Complex Environments using Large Language Models”, arXiv preprint arXiv:2406.04663, (June 2024)

Suda M, Saito T, Iwahashi N, Regan C, Oka M (2023) Simulating emergence of novelties using agent-based models. PLoS ONE 18(12): e0294228.

M. Suda, T. Saito and M. Oka, “Agent-based model using adjacent possible space for generating waves of novelty,” 2022 IEEE Symposium Series on Computational Intelligence (SSCI), Singapore, Singapore, 2022, pp. 1251-1258, doi: 10.1109/SSCI51031.2022.10022147.

T. Saito, H. Nishimura and M. Oka, “Comparative studies of evolutionary methods and RL for learning behavior of virtual creatures,” 2022 IEEE Symposium Series on Computational Intelligence (SSCI), Singapore, Singapore, 2022, pp. 1059-1065, doi: 10.1109/SSCI51031.2022.10022282.

Naoki Maejima, Takumi Saito, Mikihiro Suda and Mizuki Oka, What Factors can Affect Taking Over Members' Own Inter-organizational Social Networks in Business Firm?, NetSci2022 (poster presentation)

Mikihiro Suda, Takumi Saito, Mizuki Oka, Exploration and exploitation of the adjacent possible space for open-endedness, Proc. of the 2022 Conference on Artificial Life, Paper No: isal_a_00513, 31; 3 pages, 2022.

星野厚, 齊藤 拓己, 岡 瑞起, クラウドAIサービス推薦システムの提案,人工知能学会論文誌, vol.37(2), p. F-L65_1-8, 2022.

Atsushi Hoshino, Takumi Saito and Mizuki Oka, Inferencing the best AI service using Deep Neural Networks, Proc. of the 2nd International Conference on Information Science and System, pp.204-209, 2019.

齊藤拓己、岡瑞起、加藤和彦、色彩調和に基づく衣類コーディネートシステムの提案、2018年度人工知能学会全国大会（第32回）

齊藤拓己, 色彩調和に基づくファッションコーディネート推薦システムの提案, 2017年度筑波大学卒業論文