The paper organizes research on generalist game AI into Dataset, Model, Harness, and Benchmark pillars and charts a five-level progression from single-game mastery to agents that create and live inside game multiverses.
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AlphaExploitem adds a hierarchical transformer encoder and a diverse pool of exploitable opponents to AlphaHoldem, enabling exploitation of suboptimal poker play while preserving performance against Nash-equilibrium opponents.
citing papers explorer
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Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse
The paper organizes research on generalist game AI into Dataset, Model, Harness, and Benchmark pillars and charts a five-level progression from single-game mastery to agents that create and live inside game multiverses.
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AlphaExploitem: Going Beyond the Nash Equilibrium in Poker by Learning to Exploit Suboptimal Play
AlphaExploitem adds a hierarchical transformer encoder and a diverse pool of exploitable opponents to AlphaHoldem, enabling exploitation of suboptimal poker play while preserving performance against Nash-equilibrium opponents.