dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Experts

Pranav Ashok, Mathias Jackermeier, Jan Křetínský, Christoph Weinhuber, Maximilian Weininger, Mayank Yadav

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

Recent advances have shown how decision trees are apt data structures for concisely representing strategies (or controllers) satisfying various objectives. Moreover, they also make the strategy more explainable. The recent tool dtControl had provided pipelines with tools supporting strategy synthesis for hybrid systems, such as SCOTS and Uppaal Stratego. We present dtControl 2.0, a new version with several fundamentally novel features. Most importantly, the user can now provide domain knowledge to be exploited in the decision tree learning process and can also interactively steer the process based on the dynamically provided information. To this end, we also provide a graphical user interface. It allows for inspection and re-computation of parts of the result, suggesting as well as receiving advice on predicates, and visual simulation of the decision-making process. Besides, we interface model checkers of probabilistic systems, namely STORM and PRISM and provide dedicated support for categorical enumeration-type state variables. Consequently, the controllers are more explainable and smaller.

Original languageEnglish
Title of host publicationTools and Algorithms for the Construction and Analysis of Systems - 27th International Conference, TACAS 2021 Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021
EditorsJan Friso Groote, Kim Guldstrand Larsen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages326-345
Number of pages20
ISBN (Print)9783030720124
DOIs
StatePublished - 2021
Event27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021 Held as Part of 24th European Joint Conferences on Theory and Practice of Software, ETAPS 2021 - Virtual, Online
Duration: 27 Mar 20211 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12652 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021 Held as Part of 24th European Joint Conferences on Theory and Practice of Software, ETAPS 2021
CityVirtual, Online
Period27/03/211/04/21

Keywords

  • Controller representation
  • Decision Tree
  • Explainable Learning
  • Hybrid systems
  • Markov Decision Process
  • Probabilistic Model Checking
  • Strategy representation

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