[Submitted on 8 May 2020]
Abstract: In this paper we propose Policy Synthesis under probabilistic Constraints
(PSyCo), a systematic engineering method for synthesizing safe policies under
probabilistic constraints with reinforcement learning and Bayesian model
checking. As an implementation of PSyCo we introduce Safe Neural Evolutionary
Strategies (SNES). SNES leverages Bayesian model checking while learning to
adjust the Lagrangian of a constrained optimization problem derived from a
PSyCo specification. We empirically evaluate SNES’ ability to synthesize
feasible policies in settings with formal safety requirements.
Submission history
From: Lenz Belzner [view email]
[v1]
Fri, 8 May 2020 08:11:31 UTC (7,547 KB)
