A framework for transforming specifications in reinforcement learning

DOI10.1007/978-3-031-22337-2_29zbMath1528.68205arXiv2111.00272OpenAlexW3208792968MaRDI QIDQ6113996

Osbert Bastani, Kishor Jothimurugan, Suguman Bansal, Rajeev Alur

Publication date: 10 August 2023

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2111.00272

zbMATH Keywords

reinforcement learningtemporal logicreactive synthesis

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Markov and semi-Markov decision processes (90C40) Specification and verification (program logics, model checking, etc.) (68Q60)

Cites Work

• Near-optimal reinforcement learning in polynomial time
• \({\mathcal Q}\)-learning
• Deep reinforcement learning with temporal logics
• Faster statistical model checking for unbounded temporal properties
• Learning Algorithms for Markov Decision Processes with Average Cost
• Model Checking Probabilistic Systems
• The complexity of propositional linear temporal logics
• Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning
• Model-Free Reinforcement Learning for Stochastic Parity Games
• PAC statistical model checking for Markov decision processes and stochastic games

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