Adaptation and Assessment (TwoA) asset in C# (v1.2)

Enkhbold Nyamsuren

    Research output: Non-textual formSoftwareAcademic

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    Abstract

    Developed within the RAGE project funded by EU within Horizon2020 program. This asset enables a real-time automatic adaptation of game difficulty to player's expertise level. The adaptation algorithm makes use of a stealth assessment algorithm that assigns difficulty ratings and expertise ratings to the players and the game modules respectively. The asset tracks changes in these ratings allowing assessment of players' learning progress either by players themselves or by instructors. This is the version written in C# language. Version 1.2 includes considerable extensions to the TwoA functionalities: • API for building scenario dependency graphs • An improved scenario selection algorithm • The second module for adaptation and assessment based on continuous accuracy only • Extended parameter setting API
    Original languageEnglish
    Place of PublicationHeerlen
    PublisherOpen Universiteit Nederland
    Publication statusPublished - 23 Mar 2017

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    Keywords

    • automatic game adaptation
    • stealth assessment
    • adaptation algorithm
    • RAGE

    Cite this

    Nyamsuren, E. (Author). (2017). Adaptation and Assessment (TwoA) asset in C# (v1.2). Software, Heerlen: Open Universiteit Nederland. Retrieved from https://github.com/rageappliedgame/HatAsset/tree/1b9b82c777ac48d97bdb8868f1488819d6bb5d52