One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration

ArXi:2510.12088v2 Announce Type: replace-cross Symbolic world modeling requires inferring and representing an environment's transitional dynamics as an executable program. Prior work has focused on largely deterministic environments with abundant interaction data, simple mechanics, and human guidance. We address a realistic and challenging setting, learning in a complex, stochastic environment where the agent has only "one life" to explore a hostile environment without human guidance. We.