C. L. Buckley

Natural Induction: Spontaneous adaptive organisation without natural selection

This paper demonstrates that spontaneous adaptive organisation can arise from the interaction of physical optimisation and learning in dynamical systems, without natural selection.

An ability to respond begins with inner alignment: How phase synchronisation effects transitions to higher levels of agency

The paper uses computational models to show how phase synchronisation of microscale agents leads to emergent higher-level agency through increased problem-solving competency.

Control algorithms underlying the translational optomotor response

This paper investigates the control algorithms of the translational optomotor response in larval zebrafish through computational modeling and behavioral experiments, finding that position stabilization is partial and gain-dependent.

Learning action-oriented models through active inference

This paper shows that active inference enables efficient learning of action-oriented models by balancing goal-directed and information-seeking behaviors, avoiding sub-optimal convergence in bacterial chemotaxis.