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[2602.17594] AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games
Summary
The paper introduces the AI Gamestore, a platform for evaluating machine general intelligence through human games, highlighting its potential to surpass conventional AI benchmarks.
Why It Matters
As AI technology advances, traditional benchmarks fail to capture the complexity of human-like intelligence. The AI Gamestore offers a scalable evaluation method that could significantly enhance our understanding of machine capabilities and drive innovation in AI development.
Key Takeaways
- AI Gamestore aims to evaluate AI through a diverse range of human games.
- Current AI benchmarks are limited and often saturated, necessitating new evaluation methods.
- The platform uses LLMs and human input to create and assess new game environments.
Computer Science > Artificial Intelligence arXiv:2602.17594 (cs) [Submitted on 19 Feb 2026] Title:AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games Authors:Lance Ying, Ryan Truong, Prafull Sharma, Kaiya Ivy Zhao, Nathan Cloos, Kelsey R. Allen, Thomas L. Griffiths, Katherine M. Collins, José Hernández-Orallo, Phillip Isola, Samuel J. Gershman, Joshua B. Tenenbaum View a PDF of the paper titled AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games, by Lance Ying and 11 other authors View PDF Abstract:Rigorously evaluating machine intelligence against the broad spectrum of human general intelligence has become increasingly important and challenging in this era of rapid technological advance. Conventional AI benchmarks typically assess only narrow capabilities in a limited range of human activity. Most are also static, quickly saturating as developers explicitly or implicitly optimize for them. We propose that a more promising way to evaluate human-like general intelligence in AI systems is through a particularly strong form of general game playing: studying how and how well they play and learn to play \textbf{all conceivable human games}, in comparison to human players with the same level of experience, time, or other resources. We define a "human game" to be a game designed by humans for humans, and argue for the evaluative suitability of this space of all such games people can imagine and ...
