Towards interactive Machine Learning (iML): Applying Ant Colony Algorithms to Solve the Traveling Salesman Problem with the Human-in-the-Loop Approach

A. Holzinger, M. Plass, K. Holzinger, G. C. Crişan, C.-M. Pintea, Vasile Palade

Research output: Chapter in Book/Report/Conference proceedingChapter

56 Citations (Scopus)

Abstract

Most Machine Learning (ML) researchers focus on automatic Machine Learning (aML) where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from the availability of “big data”. However, sometimes, for example in health informatics, we are confronted not a small number of data sets or rare events, and with complex problems where aML-approaches fail or deliver unsatisfactory results. Here, interactive Machine Learning (iML) may be of help and the “human-in-the-loop” approach may be beneficial in solving computationally hard problems, where human expertise can help to reduce an exponential search space through heuristics. In this paper, experiments are discussed which help to evaluate the effectiveness of the iML-“human-in-the-loop” approach, particularly in opening the “black box”, thereby enabling a human to directly and indirectly manipulating and interacting with an algorithm. For this purpose, we selected the Ant Colony Optimization (ACO) framework, and use it on the Traveling Salesman Problem (TSP) which is of high importance in solving many practical problems in health informatics, e.g. in the study of proteins.
Original languageEnglish
Title of host publicationAvailability, Reliability, and Security in Information Systems
EditorsFrancesco Buccafurri, Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl
Place of PublicationSwitzerland
PublisherSpringer Verlag
Pages81-95
Volume9817
ISBN (Print)978-3-319-45506-8, 978-3-319-45507-5
DOIs
Publication statusPublished - 23 Aug 2016

Bibliographical note

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Keywords

  • interactive Machine Learning
  • Human-in-the-loop
  • Traveling Salesman Problem
  • Ant Colony Optimization

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