The free energy principle for action and perception: A mathematical review CL Buckley, CS Kim, S McGregor, AK Seth Journal of Mathematical Psychology 81, 55-79, 2017 | 320 | 2017 |
Learning action-oriented models through active inference A Tschantz, AK Seth, CL Buckley PLoS computational biology 16 (4), e1007805, 2020 | 97 | 2020 |
Lattice Boltzmann BGK simulation of nonlinear sound waves: the development of a shock front JM Buick, CL Buckley, CA Greated, J Gilbert Journal of Physics A: Mathematical and General 33 (21), 3917, 2000 | 80 | 2000 |
Predictive coding approximates backprop along arbitrary computation graphs B Millidge, A Tschantz, CL Buckley Neural Computation 34 (6), 1329-1368, 2022 | 77 | 2022 |
Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions RA Watson, R Mills, CL Buckley, K Kouvaris, A Jackson, ST Powers, ... Evolutionary biology 43, 553-581, 2016 | 69 | 2016 |
Neural complexity and structural connectivity L Barnett, CL Buckley, S Bullock Physical Review E 79 (5), 051914, 2009 | 68 | 2009 |
Optimization in “self‐modeling” complex adaptive systems RA Watson, CL Buckley, R Mills Complexity 16 (5), 17-26, 2011 | 60 | 2011 |
How particular is the physics of the free energy principle? M Aguilera, B Millidge, A Tschantz, CL Buckley Physics of Life Reviews 40, 24-50, 2022 | 59 | 2022 |
Scaling active inference A Tschantz, M Baltieri, AK Seth, CL Buckley 2020 international joint conference on neural networks (ijcnn), 1-8, 2020 | 59 | 2020 |
Predictive coding: a theoretical and experimental review B Millidge, A Seth, CL Buckley arXiv preprint arXiv:2107.12979, 2021 | 57 | 2021 |
Whence the expected free energy? B Millidge, A Tschantz, CL Buckley Neural Computation 33 (2), 447-482, 2021 | 57 | 2021 |
Reinforcement learning through active inference A Tschantz, B Millidge, AK Seth, CL Buckley arXiv preprint arXiv:2002.12636, 2020 | 57 | 2020 |
PID control as a process of active inference with linear generative models M Baltieri, CL Buckley Entropy 21 (3), 257, 2019 | 54 | 2019 |
Global adaptation in networks of selfish components: Emergent associative memory at the system scale RA Watson, R Mills, CL Buckley Artificial Life 17 (3), 147-166, 2011 | 54 | 2011 |
An active inference implementation of phototaxis M Baltieri, CL Buckley arXiv preprint arXiv:1707.01806, 2017 | 52 | 2017 |
Associative memory in gene regulation networks R Watson, CL Buckley, R Mills, A Davies MIT Press, 2010 | 48 | 2010 |
On the relationship between active inference and control as inference B Millidge, A Tschantz, AK Seth, CL Buckley Active Inference: First International Workshop, IWAI 2020, Co-located with …, 2020 | 47 | 2020 |
Predictions in the eye of the beholder: an active inference account of Watt governors M Baltieri, CL Buckley, J Bruineberg arXiv preprint arXiv:2006.11495, 2020 | 30 | 2020 |
“If you can't be with the one you love, love the one you're with”: How individual habituation of agent interactions improves global utility AP Davies, RA Watson, R Mills, CL Buckley, J Noble Artificial Life 17 (3), 167-181, 2011 | 30 | 2011 |
Active inference in robotics and artificial agents: Survey and challenges P Lanillos, C Meo, C Pezzato, AA Meera, M Baioumy, W Ohata, ... arXiv preprint arXiv:2112.01871, 2021 | 29 | 2021 |