Active Inference Model-Stream
Published:
Active Inference Model-Stream
I’ll be participating in the Active Inference ModelStream #001.0: “A Step-by-Step Tutorial on Active Inference” today at 11am CST. Please join me here if you would like to watch live!
About ModelStream
The ModelStream channel will aim to provide tutorials for the use of Active Inference or comparable models in describing different kinds of data. The videos for a given topic will most likely be multi-part. For today’s video, we will be covering Sections 2, 3, and 5 of this tutorial paper describing how Active Inference could be used to describe Partially Observable Markov Decision Processes (POMDP), such as may occur when an individual agent is choosing to make a binary decision while using or excluding information that is associated with risk mitigation. Importantly, the authors have provided corresponding Matlab code that directly implements the model simulations described with great detail in the tutorial paper.
As someone who does not study the neuroscience of decision-making (as a neuroscientist, I consider myself to study motor systems), I can say that this is still an excellent way to learn about how you might incorporate a process model to provide possible explanations regarding why certain data were observed. This is not a mutually exclusive process to more traditional statistical methods that use variance models to study how certain data might have arisen given the experiment and resulting observations. The two are related and both important to understand as neuroscientists seeking to assess and explain biological phenomena in a parsimonious sense.