Autonomous parsing of behavior in a multi-agent setting

D. Vanderelst, E. Barakova

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

    1 Citation (Scopus)


    Imitation learning is a promising route to instruct robotic multi-agent systems. However, imitating agents should be able to decide autonomously what behavior, observed in others, is interesting to copy. Here we investigate whether a simple recurrent network (Elman Net) can be used to extract meaningful chunks from a continuous sequence of observed actions. Results suggest that, even in spite of the high level of task specific noise, Elman nets can be used for isolating re-occurring action patterns in robots. Limitations and future directions are discussed.

    Original languageEnglish
    Title of host publicationArtificial Intelligence and Soft Computing - ICAISC 2008 - 9th International Conference, Zakopane, Poland, June 22-26. Proceedings
    EditorsL. Rutkowski, R. Tadeusiewicz, L.A. Zadeh, J.M. Zurada
    Number of pages12
    Publication statusPublished - 4 Aug 2008
    Event9th International conference on Artificial Intelligence and Soft Computing (ICAISC 2008) - Zakopane, Poland
    Duration: 22 Jun 200826 Jun 2008
    Conference number: 9

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume5097 LNAI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference9th International conference on Artificial Intelligence and Soft Computing (ICAISC 2008)
    Abbreviated titleICAISC 2008


    Dive into the research topics of 'Autonomous parsing of behavior in a multi-agent setting'. Together they form a unique fingerprint.

    Cite this