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.
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.