Second part the tutorial presented by Professor Elias Bareinboim on "Causal Reinforcement Learning", which took place at ICML-2020 (online), July 13, 2020. For further details, references, and the slides, see crl.causalai.net .
I know right, when he goes tangentially the talk gets even more interesting. I wish there was a platform where he is asked to just speak his mind, without any time limit, just outlining his interests, passion, vision etc.
53:45 For counterfactual decision-making, "Agents usually act in a reflexive manner without consider the reasons or the causes for behaving in a particular way. Whenever this is the case, they can be exploited without never realizing. " I think it is just what people do in RL as exploration, e.g., \epsilon greedy. Is there any difference or did I miss anything?
X represents a variable, whose state X is observed (i.e. you don't decide its value, you get it from data). On the opposite, do(X) represents the fact that you set deliberately the value of that variable to X (i.e. you DO an action, that corresponds to have your variable x=X)
