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Can anyone elaborate what “search” means in this context? It seems they are trying to determine the most probable Nash equilibrium but not sure what this mean when applied to RL.

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The "search" here refers to the idea that, in principle, you could search the entire space of possible hands of cards and exhaustively predict the optimal action by imagining every hand. However, like in the game of Go, this is computationally intractable, so instead they use machine learning to "guide search" towards more promising "moves". In AlphaGo (and here) this learning happened as part of a reinforcement learning pipeline.

There was some discussion of this in the AlphaGo Zero blog post from a while back: https://deepmind.com/blog/article/alphago-zero-starting-scra...

To summarize in a photo, here’s minimax search with chess: https://cdn--media--1-freecodecamp-org.cdn.ampproject.org/i/...

Imagine searching through the entire tree - billions of nodes due to the branching of chess. Now use RL to help decide where to search and branches to prune

this jpeg link downloaded a webp file to my computer and wen i try to open it it asks if im sure i want to open it. webp seems to be an image file but is it safe to open

WebP is the still image format of VP8 (like how HEIC is the still image format of x265). It's no more dangerous than any other image.

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