Christopher L. Buckley

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

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

This paper uses Active Inference to simulate and model different forms of interoceptive control, including homeostatic, allostatic, and goal-directed, and their dysfunctions.

The paper introduces μSPIM, a software platform for SPIM microscopy, enabling high-resolution volumetric imaging of live organisms like zebrafish and mice.

The paper provides a probabilistic interpretation of PID controllers using active inference, showing how they align with free energy minimization principles.