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cff-version: 1.2.0
title: >-
  ALWars: Combat-Based Evaluation of Active Learning
  Strategies
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Julius
    family-names: Gonsior
    email: julius.gonsior@tu-dresden.de
    affiliation: Technische Universität Dresden
    orcid: 'https://orcid.org/0000-0002-5985-4348'
  - given-names: Jakob
    family-names: Krude
    email: jakob.krude@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Janik
    family-names: Schönfelder
    email: janik.schonfelder@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Nick
    family-names: Lehmann
    email: nick.lehmann.@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Niccolo 
    family-names: Borgioli
    email: niccolo.Borgioli@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Paul
    family-names: Sikorski
    email: paul.sikorski@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Jessica
    family-names: Schulze
    email: jessica.schulze@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Juan Andreas
    family-names: Osorio Escobar
    email: juan_andres.osorio_escobar@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Alexander
    family-names: Krause
    email: alexander.krause@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Andreas
    family-names: Geyer
    email: andreas.geyer@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Franziskus
    family-names: Borrmann
    email: Franziskus.borrmann@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Vinzenz
    family-names: Fuhrmann
    email: vinzenz.fuhrmann@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Moritz
    family-names: Blei
    email: moritz.blei@tu-dresden.de
    affiliation: Technische Universität Dresden
  - given-names: Maik
    family-names: Thiele
    email: maik.thiele@htw-dresden.de
    affiliation: Hochschule für Technik und Wirtschaft Dresden
    orcid: 'https://orcid.org/0000-0002-1665-977X'
  - given-names: Wolfgang
    family-names: Lehner
    email: wolfgang.lehner@tu-dresden.de
    affiliation: Technische Universität Dresden
    orcid: 'https://orcid.org/0000-0001-8107-2775'
identifiers:
  - type: doi
    value: 10.1007/978-3-030-99739-7\_36
  - type: url
    value: >-
      https://link.springer.com/chapter/10.1007/978-3-030-99739-7_36
repository-code: 'https://github.com/etikedi/etikedi'
repository-artifact: 'https://wwwdb.inf.tu-dresden.de/'
abstract: >-
  The demand for annotated datasets for supervised
  machine learning (ML) projects is growing rapidly.
  Annotating a dataset often requires domain experts
  and is a timely and costly process. A premier
  method to reduce this overhead drastically is
  Active Learning (AL). Despite a tremendous
  potential for annotation cost savings, AL is still
  not used universally in ML projects. The large
  number of available AL strategies has significantly
  risen during the past years leading to an increased
  demand for thorough evaluations of AL strategies.
  Existing evaluations show in many cases
  contradicting results, without clear superior
  strategies. To help researchers in taming the AL
  zoo we present ALWars: an interactive system with a
  rich set of features to compare AL strategies in a
  novel replay view mode of all AL episodes with many
  available visualization and metrics. Under the hood
  we support a rich variety of AL strategies by
  supporting the API of the powerful AL framework
  ALiPy [21], amounting to over 25 AL strategies
  out-of-the-box.
keywords:
  - Active Learning
  - Python
  - GUI
  - Machine Learning
  - Demo
license: AGPL-3.0
date-released: '2022-04-05'