Deeply Felt Affect: The Emergence of Valence in Deep Active Inference

hello welcome to the active inference live stream this is active inference live stream number 19.0 on april first two thousand twenty one welcome to the active inference lab we are a participatory online lab that is communicating learning and practicing applied active inference you can find us at our links here this is recorded in an archived live stream so please provide us with feedback so that we can improve on our work all backgrounds and perspectives are welcome and we'll be following good video etiquette for live streams as outlined in this checklist this is the schedule that we've had so far for 2021 and the upcoming two discussions on april 6th and the 13th will be number 19.1.2 on this paper that we're going to be discussing today so right now in 19.0 the goal is to set the context and give a little background for 19.1 and 19.2 and people who are just learning about the paper which is deeply felt affect the emergence of valence in deep active inference by hesp smith parr allen firsten and ramstead in 2021 and this video is definitely just an introduction to the ideas it's meant to be a two-way on-off ramp from active inference so exposing the active inference community to ideas outside of active inference and people who might be interested in some of the bigger ideas connecting them to the active inference implementations and we have a bunch of sections planned for today in 19 so thanks a lot to stephen and to blue for helping with the slides and for coming on today so maybe we can just um introduce ourselves briefly and then we can go on to the rest of the slides we have prepared so i'm daniel i'm a postdoc in california and i'll pass this stephen hello i'm stephen i'm in toronto i'm doing a practice-based phd around social topographies and community-based development and i'll pass it over to blue hi i'm blue knight i am an independent research consultant based out of new mexico cool well i think this was a fun paper for us to read and we can just go right into what were some of the big points of the paper and the background ideas before we go through the figure and the model which will take up a lot of the time the paper is called deeply felt affect the immersion surveillance and deep active inference and it was published in the journal neural computation in 2021 and so i'll read the first one and then either of you can give a thought on that in this letter meeting paper we demonstrate that hierarchical deep bayesian networks solved using active inference afford a principled formulation of emotional valence building on both the work mentioned above as well as prior work on other emotional phenomena within the active inference framework yeah so that's just given us that insight into this idea of valence so we'll be speaking about that more but that's uh that's that's an important part of this paper i'll say the next one our hypothesis is that emotional valence can be formalized as a state of self that is inferred on the basis of fluctuations in the estimated confidence or precision an agent has in her generative model of the world that informs her decisions cool so we're going to be connecting some of the decision-making aspects of agents and inference aspects of agents to emotional balance and they're going to demonstrate it so those are the goals and the claims that they set out in the paper any thoughts blue or do you want to go to big questions and maybe introduce a big question i'll introduce you to the questions all right go for it so the big questions of this paper were how can we make more active inference models or agents that are expressive powerful realistic and interpretable what are the implications of this active inference formalizes our survival and procreation in terms of a single imperative to minimize the divergence between observed outcomes and phenotypically expected i.e preferred outcomes under a generative model that is fine-tuned over phylogeny and ontogeny thoughts on this well the first one…