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Minimax search and the structure of cognition!

Talkat !!Con West 2019 · on Monday, 2019-03-25· [machine-learning]
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Built a simple chess engine and runs a minimax search to a fixed depth using a piece count evaluation, then inspects what that brute force planner actually does and why it matters. Key claims: instrumental goals like forks emerge as shorthand not represented in code; adversarial counterfactuals produce credible threats that shape play even when predicted continuations never occur. Concrete example: the engine plays knight to g3 revealing a discovered attack and enabling capture of the rook.

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