This paper concerns the distributed intelligence or federated inference that emerges under
belief-sharing among agents who share a common world—and world model. Imagine, for …

What is a pattern? How do we come to recognize patterns never seen before? Quantifying
the notion of pattern and formalizing the process of pattern discovery go right to the heart of …

This paper considers agency in the setting of embodied or active inference. In brief, we
associate a sense of agency with prior beliefs about action and ask what sorts of beliefs …

Information processing typically occurs via the composition of modular units, such as the
universal logic gates found in discrete computation circuits. The benefit of modular …

A stochastic process' statistical complexity stands out as a fundamental property: the
minimum information required to synchronize one process generator to another. How much …

Causal asymmetry is one of the great surprises in predictive modeling: The memory required
to predict the future differs from the memory required to retrodict the past. There is a …

Renewal processes are broadly used to model stochastic behavior consisting of isolated
events separated by periods of quiescence, whose durations are specified by a given …

We apply techniques from the field of computational mechanics to evaluate the statistical
complexity of neural recording data from fruit flies. First, we connect statistical complexity to …

Predictive rate-distortion analysis suffers from the curse of dimensionality: clustering
arbitrarily long pasts to retain information about arbitrarily long futures requires resources …

A central result that arose in applying information theory to the stochastic thermodynamics of
nonlinear dynamical systems is the information-processing second law (IPSL): the physical …