• Glynatsi, N. E.; Hilbe, C.; Yohsuke, M. Exact conditions for evolutionary stability in indirect reciprocity under noise. PLOS Computational Biology, 2025.

• Lesigang, F.; Hilbe, C.; Glynatsi, N. E. Can I afford to remember less than you? Best responses in repeated additive games. Economics Letters, 2025.

• Glynatsi, N. E.; Knight, V. A.; Harper, M. Properties of winning Iterated Prisoner’s Dilemma strategies. PLOS Computational Biology, 2024.

• Glynatsi, N. E.; Akin, E.; Nowak, M. A.; Hilbe, C. Conditional cooperation with longer memory. Proceedings of the National Academy of Sciences, 2024.

• Knight, V. A.; Harper, M.; Glynatsi, N. E.; Gillard, J. Recognising and evaluating the effectiveness of extortion in the Iterated Prisoner’s Dilemma. PLOS ONE, 2024.

• Glynatsi, N. E.; McAvoy, A.; Hilbe, C. Evolution of reciprocity with limited payoff memory. Proceedings of the Royal Society B, 2024.

• Ullrich, K. K.; Glynatsi, N. E. oggmap: a Python package to extract gene ages per orthogroup and link them with single-cell RNA data. Bioinformatics, 2023.

• Traulsen, A.; Glynatsi, N. E. The future of theoretical evolutionary game theory. Philosophical Transactions of the Royal Society B, 2023.

• Glynatsi, N. E.; Knight, V. A. Game Theory and Python: An educational tutorial to game theory and repeated games using Python. Journal of Open Source Education, 2021.

• Glynatsi, N. E.; Knight, V. A. A bibliometric study of research topics, collaboration, and centrality in the iterated prisoner’s dilemma. Humanities and Social Sciences Communications, 2021.

• Glynatsi, N. E.; Knight, V. A. Using a theory of mind to find best responses to memory-one strategies. Scientific Reports, 2020.

• Glynatsi, N. E.; Knight, V. A.; Lee, T. E. An evolutionary game theoretic model of rhino horn devaluation. Ecological Modelling, 2018.

• Knight, V.; Harper, M.; Glynatsi, N. E.; Campbell, O. Evolution reinforces cooperation with the emergence of self-recognition mechanisms. PLOS ONE, 2018.

• Harper, M.; Knight, V.; Jones, M.; Koutsovoulos, G.; Glynatsi, N. E.; Campbell, O. Reinforcement learning produces dominant strategies for the Iterated Prisoner’s Dilemma. PLOS ONE, 2017.

• Knight, V. A.; Campbell, O.; Harper, M.; Langner, K. M.; Campbell, J.; Campbell, T.; Carney, A.; Chorley, M.; Davidson-Pilon, C.; Glass, K.; Glynatsi, N. E.; Ehrlich, T.; Jones, M.; Koutsovoulos, G.; Tibble, H.; Muller, J.; Palmer, G.; Petunov, P.; Slavin, P.; Standen, T.; Visintini, L.; Molden, K. An open framework for the reproducible study of the iterated prisoner’s dilemma. Journal of Open Research Software, 2016.

In preparation

• Knight, V. A.; Campbell, O.; Harper, M.; Gaffney, T. J.; Glynatsi, N. E. Reviving, reproducing, and revisiting Axelrod’s second tournament. arXiv · Preprint

• Pal, S.; Hilbe, C.; Glynatsi, N. E. The co-evolution of direct, indirect and generalized reciprocity. arXiv · Preprint

• Li, J.; Glynatsi, N. E.; Hilbe, C.; Xia, H. Tolerance and exploitation of cumulative memory strategy in direct reciprocity.