Planning with Uncertainty: Symmetries, Policy Inference, and Solution Compression 事件

Planning with Uncertainty: Symmetries, Policy Inference, and Solution Compression arXiv:2403.19883v2 Announce Type: replace Abstract: Fully-observable non-deterministic (FOND) planning is at the core of artificial intelligence planning with uncertainty. It models uncertainty through actions with non-deterministic effects. In this work, we present a collection of techniques that establish explicit best-first policy-space search as a method competitive with the state of the art for solving FOND p