Correct-by-Construction Reinforcement Learning of Cardiac Pacemakers from Duration Calculus Requirements

Authors

  • Kalyani Dole IIT Bombay
  • Ashutosh Gupta IIT Bombay
  • John Komp University of Colorado
  • Shankaranarayanan Krishna IIT Bombay
  • Ashutosh Trivedi CU Boulder

DOI:

https://doi.org/10.1609/aaai.v37i12.26728

Keywords:

General

Abstract

As the complexity of pacemaker devices continues to grow, the importance of capturing its functional correctness requirement formally cannot be overestimated. The pacemaker system specification document by \emph{Boston Scientific} provides a widely accepted set of specifications for pacemakers. As these specifications are written in a natural language, they are not amenable for automated verification, synthesis, or reinforcement learning of pacemaker systems. This paper presents a formalization of these requirements for a dual-chamber pacemaker in \emph{duration calculus} (DC), a highly expressive real-time specification language. The proposed formalization allows us to automatically translate pacemaker requirements into executable specifications as stopwatch automata, which can be used to enable simulation, monitoring, validation, verification and automatic synthesis of pacemaker systems. The cyclic nature of the pacemaker-heart closed-loop system results in DC requirements that compile to a decidable subclass of stopwatch automata. We present shield reinforcement learning (shield RL), a shield synthesis based reinforcement learning algorithm, by automatically constructing safety envelopes from DC specifications.

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Published

2023-06-26

How to Cite

Dole, K., Gupta, A., Komp, J., Krishna, S., & Trivedi, A. (2023). Correct-by-Construction Reinforcement Learning of Cardiac Pacemakers from Duration Calculus Requirements. Proceedings of the AAAI Conference on Artificial Intelligence, 37(12), 14792-14800. https://doi.org/10.1609/aaai.v37i12.26728

Issue

Section

AAAI Special Track on Safe and Robust AI