JOURNAL PUBLICATIONS

Egbert M. D., Jeong V., Postlethwaite C. M. (2020) Where computation and dynamics meet: Heteroclinic Network-based controllers in Evolutionary Robotics. in IEEE Transactions on Neural Networks and Learning Systems31(4) pp. 1084-1097, April 2020, doi: 10.1109/TNNLS.2019.2917471
Egbert, M. D., Gagnon J-S., Pérez-Mercader J. (2019) From chemical soup to computing circuit: Transforming a contiguous chemical medium into a logic gate network by modulating its external conditions. Journal of The Royal Society Interface 16(158). http://doi.org/10.1098/rsif.2019.0190 arxiv
Egbert M. D., Keane, A., Postlethwaite C. M., Wong, N. (2019) Can Signal Delay Be Functional? Including Delay In Evolved Robot Controllers. Artificial Life 25(4) 315-333.
Egbert M. D., Gruenert, G., Ibrahim B., Dittrich, P. (2019) Combining Evolution and Self-organization to Find Natural Boolean Representations in Unconventional Computational Media. Biosystems, 184, 104011.
Woolford F. M. , Egbert M. D. (2019) Behavioral Variety of a Node-Based Sensorimotor-to-Motor Map. Adaptive Behavior https://doi.org/10.1177/1059712319839061
Shitut S., Ahsendorf T., Pande S., Egbert M., Kost, C. (2019) Nanotube-mediated cross-feeding couples the metabolism of interacting bacterial cells. Environmental Microbiology doi:10.1111/1462-2920.14539
Egbert M. D., Gagnon J-S., Pérez-Mercader J. (2018) Dynamic modulation of external conditions can transform chemistry into logic gates. Journal of The Royal Society Interface, 15(144), 20180169 arxiv
Egbert M. D., Pérez-Mercader J. (2018) Methods for Measuring Viability and Evaluating Viability-Indicators. Artificial Life, 24(02), 106–118
Agmon, E., Egbert, M. D., & Virgo, N. (2018) The Biological Foundations of Enactivism: A report on a workshop held at Artificial Life XV. Artificial Life, 24(1), 49–55
Egbert M. D., Pérez-Mercader J (2016) Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations. Scientific Reports, 6, 18963
Egbert M. D., Barandiaran X. E. (2014) Modeling habits as self-sustaining patterns of sensorimotor behavior. Frontiers in Human Neuroscience, 8(590)
Barandiaran X. E., Egbert M. D. (2013) Norm-establishing and norm-following in autonomous agency. Artificial Life. 20(1):5-28
Egbert M. (2013) Bacterial Chemotaxis: Introverted or Extroverted? A Comparison of the Advantages and Disadvantages of Basic Forms of Metabolism-Based and Metabolism-Independent Behavior Using a Computational Model. PLoS ONE. 8(5):e63617
Ibrahim B., Henze R., Gruenert G., Egbert M. D., Huwald J., Dittrich P. (2013) Spatial rule-based modeling: a method and its application to the human mitotic kinetochore. Cells, 2(3): 506-544.
Egbert M. D. (2013) For Biological Systems, Maintaining Essential Variables Within Viability Limits is Not Passive – Open peer commentary on the target article "Homeostats for the 21st Century? Simulating Ashby Simulating the Brain" by Stefano Franchi. Constructivist Foundations, 9(1):109-111
Egbert M. D., Barandiaran X. E., Di Paolo E. A. (2012) Behavioral Metabolution: The Adaptive and Evolutionary Potential of Metabolism-Based Chemotaxis. Artificial Life, 18(1):1-25
Egbert M. D., Barandiaran X. E., Di Paolo E. A. (2010) A Minimal Model of Metabolism-Based Chemotaxis. PLoS Computational Biology. 6(12):e1001004
Egbert M. D., Di Paolo E. A. (2009) Integrating Autopoiesis and Behavior: An Exploration in Computational Chemo-ethology. Adaptive Behavior, 17(5):387-401

CONFERENCE PROCEEDINGS

Woolford F., Egbert M. D. (2020) A Precarious Sensorimotor Sequence Reiterator for Modelling Enactive Habits. Artificial Life Conference Proceedings, 32, 771–779.
Kolezhitskiy, Y., Egbert M. D., Postlethwaite C. (2020) Dynamical Systems Analysis of a Protocell. Artificial Life Conference Proceedings, 32, 699–701.
Egbert M. D. (2020) Marangoni Based Motile Oil-Droplets in Simulated Artificial Chemistry. Artificial Life Conference Proceedings, 32, 260–262
Egbert M. D. (2019) Real-Time Visualization and Interaction with Computational Artefacts. Abstract accepted for oral presentation at MethAL workshop at ALIFE2019.
Egbert M. D., Kolezhitskiy Y., Virgo N. (2019) Steering the Growth of Adaptive Self-Preserving Dissipative Structures. in Fellermann H., Bacardit J., Goni-Moreno A., Fuchslin M. (Eds.) The 2019 Conference on Artificial Life 2019. No. 31, 255-262
Zarco M., Egbert M. D. (2019) Different Forms of Random Motor Activity Scaffold the Formation of Different Habits in a Simulated Robot. in Fellermann H., Bacardit J., Goni-Moreno A., Fuchslin M. (Eds.) The 2019 Conference on Artificial Life. No. 31, 582-589
Egbert M. D. (2018) Investigations of an Adaptive and Autonomous Sensorimotor Individual. The 2018 Conference on Artificial Life: A Hybrid of the European Conference on Artificial Life (ECAL) and the International Conference on the Synthesis and Simulation of Living Systems (ALIFE), 343-350
Egbert M. D., Keane A., Postlethwaite C. (2017) Lag in Situated, Embodied and Dynamical Adaptive Systems. In: Advances in Artificial Life, Proceedings of the 14th European Conference on Artificial Life, ECAL, (pp. 130–137) MIT Press.
Egbert M. D., Pérez-Mercader J. (2016) Quantifying Viability. In Artificial Life 15: Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems. MIT Press.
Egbert M. D., Canamero L. (2014) Habit-based Regulation of Essential Variables. In: H. Sayama, J. Rieffel, S. Risi, R. Doursat, & H. Lipson (Eds.) Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems
Egbert M. D., Gruenert G., Escuela G., Dittrich P. (2013) Synthetic signalling protocell networks as models of neural computation. In P. Lio, O. Miglino, G. Nicosia, S. Nolfi, & M. Pavone (Eds.), Advances in Artificial Life, ECAL (pp. 248–249)
Egbert M. D., Barandiaran X. E. (2011) Quantifying Normative Behaviour and Precariousness in Adaptive Agency. In: Lenaerts T., Giacobini M., Bersini H., Bourgine P., Dorigo M. & Doursat R. (Eds.), Proceedings of the 11th European Conference on Artificial Life. MIT Press
Egbert M. D., Barandiaran X. E., Di Paolo E. A. (2010) Behavioral Metabolution: Metabolism based behavior enables new forms of adaptation and evolution. In: Fellermann H, Dorr M, Hanczyc M, Laursen LL, Maurer S, Merkle D et al., (Eds.), Artificial Life XII: Proceedings of the Twelfth International Conference on the Simulation and Synthesis of Living Systems. (pp. 213–220). MIT Press
Egbert M. D., Di Paolo E. A., Barandiaran X. E. (2009) Chemo-ethology of an Adaptive Protocell: Sensorless sensitivity to implicit viability conditions. In G. Kampis, I. Karsai, & E. Szathmary (Eds.), Advances in Artificial Life, Proceedings of the 10th European Conference on Artificial Life, ECAL. (pp. 242–250).Springer, Berlin
Virgo N., Egbert M. D., Froese T. (2009) The Role of the Spatial Boundary in Autopoiesis. In: Proceedings of the Tenth European Conference on Artificial Life, ECAL09. (pp. 234–242), Budapest, Springer Verlag
Egbert M. D., Di Paolo E. A. (2008) Mechanisms of adaptation to periodic environmental change. In M. Schlesinger, L. Berthouze, & C. Balkenius (Eds.), Proceedings of the Eighth International Conference on Epigenetic Robotics (Vol. 139, pp. 141–142)Lund University Cognitive Studies

OTHER

Egbert M. D. (forthcoming 2020) Robots are machines and thus are both super-human and sub-human. Chapter in J. Cejkova (Ed.), Robot100 a book that marks the 100th anniversary of the word "robot" with a collection of essays from scientists and other disciplines.
Virtual Seminar Series (2020--ongoing) Artificial Life Seminars Series.
Egbert M. D. (2019) Realtime Visualization and Interaction Toolkit Source Code. This is a free Python-based framework built on top of http://kivy.org that I developed to visualize and interact with my computational models.
Virtual Seminar Series (2015--ongoing) ENSO Seminars. A collaboration with Marek McGann.