A key problem for accounts of blankets and boundaries I have seen on LW so far is the following elementary problem (from the paper): ”Therefore, the MB [Markov Blanket] formalism forbids interdependencies induced by past events that are kept in memory, but may not directly influence the present state of the blankets.
Thanks to Fernando Rosas telling me about this paper.
Is my intuition correct that in the MB formalism, past events that are causally linked to are not included in the Markov Blanket, but the node corresponding to the memory state still is included in the MB?
That is, the influence of the past event is mediated by a node corresponding to having memory of that past event?
Well, past events—before some time t—kind of obviously can’t be included in the Markov blanket at time t.
As far as I understand it, the MB formalism captures only momentary causal interactions between “Inside” and “Outside” but doesn’t capture a kind of synchronicity/fine-tuning-ish statistical dependency that doesn’t manifest in the current causal interactions (across the Markov blanket) but is caused by past interactions.
For example, if you learned a perfect weather forecast for the next month and then went into a completely isolated bunker but kept track of what day it was, your beliefs and the actual weather would be very dependent even though there’s no causal interaction (after you entered the bunker) between your beliefs and the weather. This is therefore omitted by MBs and CBs want to capture that.
Current work on Markov blankets and Boundaries on LW is flawed and outdated. State of the art should factor through this paper on Causal Blankets; https://iwaiworkshop.github.io/papers/2020/IWAI_2020_paper_22.pdf
A key problem for accounts of blankets and boundaries I have seen on LW so far is the following elementary problem (from the paper):
”Therefore, the MB [Markov Blanket] formalism forbids interdependencies induced by past events that are kept in memory, but may not directly influence the present state of the blankets.
Thanks to Fernando Rosas telling me about this paper.
You may want to make this a linkpost to that paper as that can then be tagged and may be noticed more widely.
I have only skimmed the paper.
Is my intuition correct that in the MB formalism, past events that are causally linked to are not included in the Markov Blanket, but the node corresponding to the memory state still is included in the MB?
That is, the influence of the past event is mediated by a node corresponding to having memory of that past event?
Well, past events—before some time t—kind of obviously can’t be included in the Markov blanket at time t.
As far as I understand it, the MB formalism captures only momentary causal interactions between “Inside” and “Outside” but doesn’t capture a kind of synchronicity/fine-tuning-ish statistical dependency that doesn’t manifest in the current causal interactions (across the Markov blanket) but is caused by past interactions.
For example, if you learned a perfect weather forecast for the next month and then went into a completely isolated bunker but kept track of what day it was, your beliefs and the actual weather would be very dependent even though there’s no causal interaction (after you entered the bunker) between your beliefs and the weather. This is therefore omitted by MBs and CBs want to capture that.