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Discussion (6 Comments)Read Original on HackerNews
In this case, he excluded the dog’s veto behavior. But if you tried to model that too, it would also be interesting.
It really is a difficult profession.
A plan with options might handle that, but that makes it trickier to satisfy the novelty constraint if each days plan needs to account for what was made on the previous day. Could be interesting to see what a plan with optionality looks like!
As you said, if Bebop refuses to go home, then the model has to remember the previous state, and the difficulty increases a lot. Usually, this kind of thing would be modeled with Markov rewards, using states and transition probabilities.
It is a fun problem. I really enjoy writing like this because it always gives me something worth thinking about.
My one criticism of your post is it needs more pics of the greyhound!
Whenever I sit down with a few spare minutes to try it, my lurcher appears and wants a walk :-)