\(L^\ast\)-based learning of Markov decision processes (extended version)
type: Item
instance of: scholarly article
title: \(L^\ast\)-based learning of Markov decision processes (extended version)
author: Martin Tappler
author: Bernhard K. Aichernig
author: Giovanni Bacci
author: Maria Eichlseder
author: Kim G. Larsen
published in: Formal Aspects of Computing
publication date: 2021-09-14T00:00:00Z
full work available at URL: https://arxiv.org/abs/1906.12239
Mathematics Subject Classification ID: 68-XX
zbMATH DE Number: 7395145
zbMATH Keywords: model inference
zbMATH Keywords: active automata learning
zbMATH Keywords: Markov decision processes
describes a project that uses: PRISM
describes a project that uses: BisimDist
describes a project that uses: prob-black-reach
describes a project that uses: NModel
MaRDI profile type: Publication
OpenAlex ID: W3132992873
cites work: Fast randomized consensus using shared memory
cites work: Learning regular sets from queries and counterexamples
cites work: Efficient active automata learning via mutation testing
cites work: Probabilistic black-box reachability checking (extended version)
cites work: On-the-Fly Exact Computation of Bisimilarity Distances
cites work: Computing Behavioral Distances, Compositionally
cites work: Q5322945
cites work: Learning Behaviors of Automata from Multiplicity and Equivalence Queries
cites work: Learning Probability Distributions Generated by Finite-State Machines
cites work: Active learning for extended finite state machines
cites work: Testing Software Design Modeled by Finite-State Machines
cites work: Learning deterministic regular grammars from stochastic samples in polynomial time
cites work: Q3404129
cites work: Learning-Based Compositional Verification for Synchronous Probabilistic Systems
cites work: Q544454
cites work: Computer Aided Verification
cites work: Probability Inequalities for Sums of Bounded Random Variables
cites work: Efficient noise-tolerant learning from statistical queries
cites work: Automated Verification and Strategy Synthesis for Probabilistic Systems
cites work: Learning Probabilistic Systems from Tree Samples
cites work: Learning deterministic probabilistic automata from a model checking perspective
cites work: Linear Automaton Transformations
cites work: Q4315289
cites work: Inference of finite automata using homing sequences
cites work: Validation of Stochastic Systems
cites work: FM 2009: Formal methods. Second world congress, Eindhoven, The Netherlands, November 2--6, 2009. Proceedings
cites work: Q4847023
cites work: Q3395949
cites work: Q4896913
cites work: Learning probabilistic automata and Markov chains via queries
cites work: A theory of the learnable
DOI: 10.1007/S00165-021-00536-5
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description: scientific article; zbMATH DE number 7395145