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Learning interactive learning strategy with genetic algorithm

Jan Hanzel (2014) Learning interactive learning strategy with genetic algorithm. EngD thesis.

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    The main goal of this thesis was to develop an algoritem for learning the best strategy in the case of interactive learning between a human and a robot. We presented the definition and formalization of a learning strategy. A learning strategy specifies the behaviour of a student and a teacher in a interactive learning process. We also presented a genetic algorithm to resolve our optimisation problem. We tryed to inpruve vectors which are used to present learning strategies. The vectors were evaluated, crossed and mutated each iteration. For evaluation of the vectors we used recognition score which measures how successful was the algorithm at recognizing a specific concept after learning it by using a specific strategy. We also used tutoring cost to measure the tutor involvment in the learning process. The results show that the quality of the strategies increases each iteration. We notice the inprovement as an increase in the recognition score and decrease of tutoring cost.

    Item Type: Thesis (EngD thesis)
    Keywords: Interactive learning, learning strategies, genetic algorithm.
    Number of Pages: 55
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Danijel Skočaj296Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1536177603 )
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 2827
    Date Deposited: 15 Oct 2014 15:19
    Last Modified: 29 Jan 2015 13:35
    URI: http://eprints.fri.uni-lj.si/id/eprint/2827

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