mlsanityData to 7 Oct 2026

Funnel-based Reward Shaping for Signal Temporal Logic Tasks in Reinforcement Learning

arXiv 2212.03181 ↗First posted 30 Nov 2022eess.SY cs.AI cs.LGcited by 4

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Abstract (arXiv)

Signal Temporal Logic (STL) is a powerful framework for describing the complex temporal and logical behaviour of the dynamical system. Numerous studies have attempted to employ reinforcement learning to learn a controller that enforces STL specifications; however, they have been unable to effectively tackle the challenges of ensuring robust satisfaction in continuous state space and maintaining tractability. In this paper, leveraging the concept of funnel functions, we propose a tractable reinforcement learning algorithm to learn a time-dependent policy for robust satisfaction of STL specification in continuous state space. We demonstrate the utility of our approach on several STL tasks using different environments.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 12 of its 25 references that are in the map. First posted on arXiv 30 Nov 2022.

Builds on

12 of 25 references.

References · 12

  1. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,302
  2. 2018DeepMind Control Suitecited by 935
  3. 2018Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Researchcited by 256
  4. 2016Reinforcement Learning With Temporal Logic Rewardscited by 114
  5. 2016Q-Learning for Robust Satisfaction of Signal Temporal Logic Specificationscited by 65
  6. 2019A Finite-Time Analysis of Q-Learning with Neural Network Function Approximationcited by 47
  7. 2020Tractable Reinforcement Learning of Signal Temporal Logic Objectivescited by 21
  8. 2017A Policy Search Method For Temporal Logic Specified Reinforcement Learning Taskscited by 19
  9. 2022Deep reinforcement learning under signal temporal logic constraints using Lagrangian relaxationcited by 8
  10. 2022A policy gradient approach for Finite Horizon Constrained Markov Decision Processescited by 8
  11. 2017Prescribed Performance Control for Signal Temporal Logic Specificationscited by 3
  12. 2019Prescribed Performance Control Guided Policy Improvement for Satisfying Signal Temporal Logic Taskscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026ReasonSTL: Bridging Natural Language and Signal Temporal Logic via Tool-Augmented Process-Rewarded Learningcited by 1
  2. 2026Specification-Aware Distribution Shaping for Robotics Foundation Modelscited by 0
  3. 2026GraSP-STL: A Graph-Based Framework for Zero-Shot Signal Temporal Logic Planning via Offline Goal-Conditioned Reinforcement Learningcited by 0
  4. 2026Reward Machines for Signal Temporal Logiccited by 0