claim

active

claim:active-inference-describes-the-dynamics-of-systems-that-persist-at-non-equilibrium-steady-state-and-that-can-be-statistically-segregated-from-their-environment-via-a-markov-blanket

Active inference describes the dynamics of systems that persist at non-equilibrium steady-state and that can be statistically segregated from their environment via a Markov blanket.

Sets the theoretical grounding in Section 2.

Source paper

extracted_from

Active inference on discrete state-spaces: a synthesis

(2020) · Lancelot Da Costa · Thomas Parr · Noor Sajid · Sebastijan Veselic +2

Neighborhood — ranked by edge-count

Communities (2)

community

Active inference & agent ecology
members_of
Free energy minimization, Markov blankets, trust gradients, and multi-agent rhythm/deferral frameworks
Active inference & free energy minimization
members_of
Friston's framework unifying perception, action, and learning under variational free energy minimization.

Frameworks (1)

framework

Free Energy Principle
supports
A foundational variational principle from statistical physics that formalizes how self-organizing systems maintain structural integrity and adapt to their environment by minimizing free energy—a mathematical bound on surprise or prediction error. Originally developed by Karl Friston, the framework unifies action, perception, and learning as processes of active inference, where systems both update internal models of the world and act upon it to reduce the divergence between predictions and observations.

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Active inference offers an attractive natural adaptation mechanism for non-stationary environments due to its Bayesian model updating properties.claim0.873
§3, after non-stationary results.
Active inference achieves Bayes-optimal behavior in non-stationary environments through online belief updating.hypothesis0.848
Tested via FrozenLake experiments; predicts superior performance when environment dynamics change.
Active inference provides a framework (derived from first principles) for solving and understanding the behavior of autonomous agents.claim0.843
Active inference is a normative principle underwriting perception, action, planning, decision-making and learning in biological or artificial agents.quote0.838
"active inference separates the problems of optimizing action and perception by assuming that action fulfills predictions based on inferred states"quote0.832
Active inference has no random or stochastic aspects; everything changes to minimize variational free energy in accord with Hamilton's principle of least action.claim0.832
Ontological claim about the deterministic nature of active inference agents in these simulations
"Active inference is a self-organising process of action policy selection."quote0.830
These dynamics are consistent with predictive processing since active inference prescribes dynamics that minimise prediction error.concept0.829
Connection between active inference neuronal dynamics and predictive processing theory.