• DocumentCode
    3683509
  • Title

    Testing reliability of replay-based imitation for StarCraft

  • Author

    In-Seok Oh;Kyung-Joong Kim

  • Author_Institution
    Dept. of Computer Science and Engineering, Sejong University, Seoul, South Korea
  • fYear
    2015
  • Firstpage
    536
  • Lastpage
    537
  • Abstract
    For StarCraft, it´s easy to download lots of replays from gaming portals. Using simple tools, it´s possible to extract all the gaming events stored in the replays. At each frame, it can tell us the human player´s decision making given game states. Instead of making hard-coded AIs, it´s promising to imitate the human player´s decision recorded in the replays. In this study, we propose to create an AI bot imitates human player´s high-level decisions (attack or retreat) on a group of units from replays. As a first step, we tested the reliability of the imitation system using replays from portals. We reported the ratio of apparent mistakes from the imitation system and the way to reduce the error.
  • Keywords
    "Reliability","Games","Artificial intelligence","Decision making","Portals","Filtering","Testing"
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Games (CIG), 2015 IEEE Conference on
  • ISSN
    2325-4270
  • Electronic_ISBN
    2325-4289
  • Type

    conf

  • DOI
    10.1109/CIG.2015.7317899
  • Filename
    7317899