Policy Optimization with Linear Temporal Logic Constraints

• URL: http://arxiv.org/abs/2206.09546v1
• Date: Mon, 20 Jun 2022 02:58:02 GMT
• Title: Policy Optimization with Linear Temporal Logic Constraints
• Authors: Cameron Voloshin, Hoang M. Le, Swarat Chaudhuri, Yisong Yue
• Abstract summary: We study the problem of policy optimization with linear temporal logic constraints. We develop a model-based approach that enjoys a sample complexity analysis for guaranteeing both task satisfaction and cost optimality.
• Score: 37.27882290236194
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We study the problem of policy optimization (PO) with linear temporal logic (LTL) constraints. The language of LTL allows flexible description of tasks that may be unnatural to encode as a scalar cost function. We consider LTL-constrained PO as a systematic framework, decoupling task specification from policy selection, and an alternative to the standard of cost shaping. With access to a generative model, we develop a model-based approach that enjoys a sample complexity analysis for guaranteeing both task satisfaction and cost optimality (through a reduction to a reachability problem). Empirically, our algorithm can achieve strong performance even in low sample regimes.

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