| A technical critique of some parts of the free energy principle M Biehl, FA Pollock, R Kanai Entropy 23 (3), 293, 2021 | 88 | 2021 |
| A strategy for origins of life research C Scharf, N Virgo, HJ Cleaves, M Aono, N Aubert-Kato, A Aydinoglu, ... Astrobiology 15 (12), 1031-1042, 2015 | 82 | 2015 |
| Information generation as a functional basis of consciousness R Kanai, A Chang, Y Yu, I Magrans de Abril, M Biehl, N Guttenberg Neuroscience of consciousness 2019 (1), niz016, 2019 | 71 | 2019 |
| Interaction learning for dynamic movement primitives used in cooperative robotic tasks T Kulvicius, M Biehl, MJ Aein, M Tamosiunaite, F Wörgötter Robotics and Autonomous Systems 61 (12), 1450-1459, 2013 | 68 | 2013 |
| Information closure theory of consciousness AYC Chang, M Biehl, Y Yu, R Kanai Frontiers in Psychology 11, 1504, 2020 | 66 | 2020 |
| Causal blankets: Theory and algorithmic framework FE Rosas, PAM Mediano, M Biehl, S Chandaria, D Polani International workshop on active inference, 187-198, 2020 | 52 | 2020 |
| Expanding the active inference landscape: more intrinsic motivations in the perception-action loop M Biehl, C Guckelsberger, C Salge, SC Smith, D Polani Frontiers in neurorobotics 12, 45, 2018 | 46 | 2018 |
| Interpreting systems as solving POMDPs: a step towards a formal understanding of agency M Biehl, N Virgo International Workshop on Active Inference, 16-31, 2022 | 27 | 2022 |
| Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems M Biehl, T Ikegami, D Polani Proceedings of the Artificial Life Conference 2016, 722, 2016 | 27 | 2016 |
| Interpreting dynamical systems as Bayesian reasoners N Virgo, M Biehl, S McGregor Joint European conference on machine learning and knowledge discovery in …, 2021 | 23 | 2021 |
| Investigating transformational complexity: Counting functions in elementary cellular automata regions M Biehl, O Witkowski Complexity. https://doi. org/10.1155/2021/7501405, 2021 | 16 | 2021 |
| Modular robot control environment testing neural control on simulated and real robots F Hesse, G Martius, P Manoonpong, M Biehl, F Wörgötter Frontiers in Computational Neuroscience, Conference Abstract: Bernstein …, 2012 | 9 | 2012 |
| Action and perception for spatiotemporal patterns M Biehl, D Polani 14th European Conference on Artificial Life 2017 14, 68-75, 2017 | 8 | 2017 |
| A bayesian interpretation of the internal model principle M Baltieri, M Biehl, M Capucci, N Virgo arXiv preprint arXiv:2503.00511, 2025 | 7 | 2025 |
| Formal approaches to a definition of agents M Biehl arXiv preprint arXiv:1704.02716, 2017 | 6 | 2017 |
| Specific and complete local integration of patterns in Bayesian networks M Biehl, T Ikegami, D Polani Entropy 19 (5), 230, 2017 | 5 | 2017 |
| A “good regulator theorem” for embodied agents N Virgo, M Biehl, M Baltieri, M Capucci Artificial Life Conference Proceedings 37 2025 (1), 46, 2025 | 4 | 2025 |
| Embracing sensorimotor history: Time-synchronous and time-unrolled Markov blankets in the free-energy principle N Virgo, FE Rosas De Andraca, M Biehl University of Sussex, 2022 | 3 | 2022 |
| Investigating transformational complexity: Counting functions a region induces on another in elementary cellular automata M Biehl, O Witkowski Complexity 2021 (1), 7501405, 2021 | 3 | 2021 |
| Dynamics of a bayesian hyperparameter in a markov chain M Biehl, R Kanai International Workshop on Active Inference, 35-41, 2020 | 3 | 2020 |
Ryota KanaiAraya, Inc.Verified email at araya.org
