Michelangelo Naim

Benchmarking World-Model Learning with Environment-Level Queries

World models are central to building AI agents capable of flexible reasoning and planning. Yet current evaluations (i) test only properties measurable from observed interactions within an environment, such as next-frame prediction or task return, and (ii) do not test whether a learned model supports…