Data-Driven Decision Theory for Player Analysis in Pacman

Benjamin Cowley, Darryl Charles, Michaela M Black, Ray J Hickey

    Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

    Kuvaus

    Computer and videogames have been described using several formal systems – in this paper we consider them as Information Systems. In particular, we use a Decision Theoretic approach to model and analyse off-line, data from PacmanTM players. Our method attempts to calculate the optimal choices available to a player based on key utilities for a given game state. Our hypothesis in this approach is that observing a player’s deviation from the optimal choices predicted can reveal their play preferences and skill, and thus form a basic player classifier. The method described builds on work done in [Cowley et al 2006], increasing the scope and sophistication of the model by decreasing reliance on supervision. The downside is a consequent performance hit, which prevents real-time execution of the modelling algorithm. In this paper we outline the basic principle of the Decision Theoretic approach and discuss the results of our evolution toward data-driven classification. Introduction
    Alkuperäiskielienglanti
    OtsikkoProceedings of Articifical Intelligence in Interactive Digital Entertainment 2007 : Optimizing Player Satisfaction Workshop
    ToimittajatGeorgios Yannakakis
    Sivumäärä6
    JulkaisupaikkaPalo Alto
    KustantajaAAAI Press
    Julkaisupäivä2007
    Sivut25-30
    TilaJulkaistu - 2007
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa

    Lainaa tätä

    Cowley, B., Charles, D., Black, M. M., & Hickey, R. J. (2007). Data-Driven Decision Theory for Player Analysis in Pacman. teoksessa G. Yannakakis (Toimittaja), Proceedings of Articifical Intelligence in Interactive Digital Entertainment 2007: Optimizing Player Satisfaction Workshop (Sivut 25-30). Palo Alto: AAAI Press.
    Cowley, Benjamin ; Charles, Darryl ; Black, Michaela M ; Hickey, Ray J. / Data-Driven Decision Theory for Player Analysis in Pacman. Proceedings of Articifical Intelligence in Interactive Digital Entertainment 2007: Optimizing Player Satisfaction Workshop. Toimittaja / Georgios Yannakakis. Palo Alto : AAAI Press, 2007. Sivut 25-30
    @inproceedings{8b257189f51f4ec7a59a56376741846d,
    title = "Data-Driven Decision Theory for Player Analysis in Pacman",
    abstract = "Computer and videogames have been described using several formal systems – in this paper we consider them as Information Systems. In particular, we use a Decision Theoretic approach to model and analyse off-line, data from PacmanTM players. Our method attempts to calculate the optimal choices available to a player based on key utilities for a given game state. Our hypothesis in this approach is that observing a player’s deviation from the optimal choices predicted can reveal their play preferences and skill, and thus form a basic player classifier. The method described builds on work done in [Cowley et al 2006], increasing the scope and sophistication of the model by decreasing reliance on supervision. The downside is a consequent performance hit, which prevents real-time execution of the modelling algorithm. In this paper we outline the basic principle of the Decision Theoretic approach and discuss the results of our evolution toward data-driven classification. Introduction",
    author = "Benjamin Cowley and Darryl Charles and Black, {Michaela M} and Hickey, {Ray J}",
    note = "Volume: Technical Proceeding volume:",
    year = "2007",
    language = "English",
    pages = "25--30",
    editor = "Georgios Yannakakis",
    booktitle = "Proceedings of Articifical Intelligence in Interactive Digital Entertainment 2007",
    publisher = "AAAI Press",
    address = "United States",

    }

    Cowley, B, Charles, D, Black, MM & Hickey, RJ 2007, Data-Driven Decision Theory for Player Analysis in Pacman. julkaisussa G Yannakakis (Toimittaja), Proceedings of Articifical Intelligence in Interactive Digital Entertainment 2007: Optimizing Player Satisfaction Workshop. AAAI Press, Palo Alto, Sivut 25-30.

    Data-Driven Decision Theory for Player Analysis in Pacman. / Cowley, Benjamin; Charles, Darryl; Black, Michaela M; Hickey, Ray J.

    Proceedings of Articifical Intelligence in Interactive Digital Entertainment 2007: Optimizing Player Satisfaction Workshop. toim. / Georgios Yannakakis. Palo Alto : AAAI Press, 2007. s. 25-30.

    Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

    TY - GEN

    T1 - Data-Driven Decision Theory for Player Analysis in Pacman

    AU - Cowley, Benjamin

    AU - Charles, Darryl

    AU - Black, Michaela M

    AU - Hickey, Ray J

    N1 - Volume: Technical Proceeding volume:

    PY - 2007

    Y1 - 2007

    N2 - Computer and videogames have been described using several formal systems – in this paper we consider them as Information Systems. In particular, we use a Decision Theoretic approach to model and analyse off-line, data from PacmanTM players. Our method attempts to calculate the optimal choices available to a player based on key utilities for a given game state. Our hypothesis in this approach is that observing a player’s deviation from the optimal choices predicted can reveal their play preferences and skill, and thus form a basic player classifier. The method described builds on work done in [Cowley et al 2006], increasing the scope and sophistication of the model by decreasing reliance on supervision. The downside is a consequent performance hit, which prevents real-time execution of the modelling algorithm. In this paper we outline the basic principle of the Decision Theoretic approach and discuss the results of our evolution toward data-driven classification. Introduction

    AB - Computer and videogames have been described using several formal systems – in this paper we consider them as Information Systems. In particular, we use a Decision Theoretic approach to model and analyse off-line, data from PacmanTM players. Our method attempts to calculate the optimal choices available to a player based on key utilities for a given game state. Our hypothesis in this approach is that observing a player’s deviation from the optimal choices predicted can reveal their play preferences and skill, and thus form a basic player classifier. The method described builds on work done in [Cowley et al 2006], increasing the scope and sophistication of the model by decreasing reliance on supervision. The downside is a consequent performance hit, which prevents real-time execution of the modelling algorithm. In this paper we outline the basic principle of the Decision Theoretic approach and discuss the results of our evolution toward data-driven classification. Introduction

    M3 - Conference contribution

    SP - 25

    EP - 30

    BT - Proceedings of Articifical Intelligence in Interactive Digital Entertainment 2007

    A2 - Yannakakis, Georgios

    PB - AAAI Press

    CY - Palo Alto

    ER -

    Cowley B, Charles D, Black MM, Hickey RJ. Data-Driven Decision Theory for Player Analysis in Pacman. julkaisussa Yannakakis G, toimittaja, Proceedings of Articifical Intelligence in Interactive Digital Entertainment 2007: Optimizing Player Satisfaction Workshop. Palo Alto: AAAI Press. 2007. s. 25-30