> "Unlike many recent important breakthroughs in A.I Research, like Deepmind’s AlphaGo, CFR does not rely on Neural Networks to calculate probabilities or the v

> "Unlike many recent important breakthroughs in A.I Research, like Deepmind’s AlphaGo, CFR does not rely on Neural Networks to calculate probabilities or the value of a particular move. Instead by playing itself over millions if not billions of games, it can begin to sum up the total amount of regret for each action it has taken in particular positions." If the goal is to build a general-purpose AI, this approach seems like a dead-end. The distinguishing feature of a general-purpose AI is knowing what to do when it encounters novel situations. In contrast, the CFR algorithm above sounds more like a training program where the "AI" teaches itself using empirical results, what to do for every single scenario. Such an empirical approach may work well for scenarios that have been frequently encountered in the past, but when dealing with novel scenarios, it seems to me that a deductive approach is what's truly needed.