rapfff / jajapy

Baum-Welch for all kind of Markov models

Introduction

jajapy is a python library implementing the Baum-Welch algorithm on various kinds of Markov models. jajapy generates models which are compatible with the Stormpy model checker. Thus, jajapycan be use as a learning extension to the Storm model checker.

Main features

jajapy provides:

Markov Model	Learning Algorithm(s)
MC	Baum-Welch for MCs Alergia (ref)
MDP	Baum-Welch for MDPs (ref) Active Baum-Welch (ref) IOAlergia (ref)
CTMC	Baum-Welch for CTMCs Baum-Welch for synchronous compositions of CTMCs
PCTMC	Baum-Welch for PCTMCs (ref)
HMM	Baum-Welch for HMMs (ref)
GoHMM	Baum-Welch for GoHMMs (ref)

jajapy is compatible with Prism and Storm.

Installation

pip install jajapy

Requirements

• numpy
• scipy
• alive-progress
• sympy
• stormpy (recommended: if stormpy is not installed, jajapy will generate models in jajapy format).

Documentation

Available on readthedoc

Reference and citation

• The extended version of the tool paper presented at QEST'23 is available here
• If you use this tool in your research, please cite it

About the author

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