counter factual regret minimization
Counter factual regret minimization is a way of helping a computer take decisions by predicting what would have happened if the computer had made a different decision. The idea is that, if the computer can figure out what would have been the best decision, it can choose the decision that would give the best outcome more often.
To do this, the computer uses lots of data to figure out what kind of decision it would have made in the past, and what the outcome of those decisions would have been. It can then use that information to decide which decision it should make now, based on the best outcome it could expect.
To do this, the computer uses lots of data to figure out what kind of decision it would have made in the past, and what the outcome of those decisions would have been. It can then use that information to decide which decision it should make now, based on the best outcome it could expect.