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These are my thoughts on zero sum games. From poker to quant trading. Zero-sum games are fundamentally informational contests. The GTO (unexploitable) strategy is often suboptimal in practice because it is either unimplementable or even unknown and assumes everyone else is playing optimally. The GTO strategy is not maximally exploitative it is minimally exploited. In a game of non-optimal participants, the GTO strategy is not guaranteed to be the one that makes the most money.
🎥 New in Computational Game Theory! Lessons 16 & 17 are now live:
🚀 Lesson 16: Pruning Algorithms in Game Tree Search - Minimax & AlphaBeta pruning for zero-sum games like chess: https://youtu.be/-JsmSbB5XSU
🤔 Lesson 17: Imperfect Information Games - Info sets, simultaneous moves, & strategy under uncertainty: https://youtu.be/1Aq_OBKVzb4
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📚 Lessons 12 & 13 of Computational Game Theory are now live!
🎥 Lesson 12: Rationalizability & Correlated Equilibria
🎥 Lesson 13: Maximin & Minimax Strategies
Explore how rationalizability and correlated equilibrium extend Nash equilibrium, and learn about maximin/minimax strategies in zero-sum games. Watch the lessons here:
Lesson 12: https://youtu.be/5E1CZItnQ_o
Lesson 13: https://youtu.be/asODU0tTnW0
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