A Message Passing Perspective on Planning Under Active Inference

Magnus T. Koudahl, Christopher L. Buckley, Bert de Vries

Abstract: We present a message passing interpretation of planning under Active Inference. Specifically, we show how the Active Inference planning procedure can be broken into a (partial) message passing sweep over a graph, followed by local computations of a cost functional (the Expected Free Energy). Using Forney-style Factor Graphs, we then proceed to show how one can derive novel planning schemes by local changes to the underlying graph and message passing schedule. We illustrate this by first isolating the “sophisticated” aspect of Sophisticated Inference and then proposing a novel planning algorithm through combining the sophisticated update mechanism with a different message passing schedule. Our main contribution is a modular view of planning under Active Inference that can serve as a framework for both understanding existing algorithms, deriving new ones and extending the class of models that are amenable to Active Inference. Approaching Active Inference from a message passing perspective also shows how it can be efficiently implemented using off-the-shelf probabilistic programming software, broadening the class of models available to researchers and practitioners.