The answer
It assigned probabilities to possible moves from a board position. That guidance helped the system focus its search on moves considered more promising.
How did AlphaGo use supervised learning and reinforcement learning?
What did AlphaGo's policy network predict?
More FAQs in How did AlphaGo use supervised learning and reinforcement learning?
Move selection and position evaluation are different tasks. A value estimate helps assess how favorable a position is without fully exploring every possible continuation.
No. The original system used expert games in supervised training. The later AlphaGo Zero system removed that dependency and learned from self-play instead.
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