How did AI improve for poker?

AI has significantly improved in the realm of poker through several advancements and approaches:

1. Algorithmic Advances: Rather than relying solely on precomputed strategies, AI evolved to use real-time search-based methods. This approach enabled the AI to compute better strategies during gameplay rather than relying on a static game plan. For instance, the transition from the 2015 approach to the 2017 method saw the AI perform much better against top players due to this shift in strategy 1.

2. Training and Self-Play: Initial AI systems performed extensive self-play to develop strategies. However, these systems lacked the ability to adapt during actual games, which human players do through real-time thinking and planning. By incorporating human-like intuition and real-time strategy adjustments, the AI's performance became more competitive 2.

3. Absence of Neural Networks: Interestingly, early successful poker AI (like Libratus) did not heavily rely on neural networks. The challenge wasn't in feature extraction but in designing a scalable algorithm for balanced strategy. Modern poker AI now uses neural nets more comprehensively to model complex value functions that account for players' beliefs about their opponents' hands 3.

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     AI Poker Competition

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     2

     Bot vs. Human Strategy

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     3

     Poker AI Insights

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     4

     Poker's Evolving Strategy

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4. Impact on Training and Strategy: AI's integration into poker has revolutionized the game. Top professional players now train with AI to refine their strategies and identify mistakes. This computational assistance has elevated the overall skill level in poker. For example, Daniel Negreanu has been noted for continuously updating his strategies with AI advances, demonstrating how top players adapt 4.

5. Human-like Play: Efforts are being made to create AI that plays in a more human-like manner, making it a more relatable and realistic opponent. Techniques from developing diplomacy AI have been applied to chess and Go, resulting in bots that exhibit human-like strategic thinking. This approach also allows for adjusting the AI to play at different skill levels similar to specific human players 5.

These developments have not only improved AI's performance in poker but also transformed how the game is played and taught, making it a more sophisticated and strategic endeavor for human players.