Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models (ACES) Introduction Human intelligence is marked not just by the ability to solve problems, but by the creative act of inventing them. Automating the generation of novel, diverse, and challenging problems has wide-ranging applications-from personalized education to robust benchmarking of AI systems. The ACES (Autotelic CodE Search) framework, accepted as a Spotlight Poster 💫 at NeurIPS 2024, introduces a principled method for generating Python programming puzzles that are both difficult and semantically varied, pushing the boundaries of what current generative models can achieve alone. ...