General General Game AI

被引:0
|
作者
Togelius, Julian [1 ]
Yannakakis, Georgios N. [2 ]
机构
[1] NYU, Tandon Sch Engn, 550 1St Ave, New York, NY 10003 USA
[2] Univ Malta, Inst Digital Games, Msida, Malta
关键词
AUDIO;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Arguably the grand goal of artificial intelligence research is to produce machines with general intelligence: the capacity to solve multiple problems, not just one. Artificial intelligence (AI) has investigated the general intelligence capacity of machines within the domain of games more than any other domain given the ideal properties of games for that purpose: controlled yet interesting and computationally hard problems. This line of research, however, has so far focused solely on one specific way of which intelligence can be applied to games: playing them. In this paper, we build on the general game-playing paradigm and expand it to cater for all core AI tasks within a game design process. That includes general player experience and behavior modeling, general non-player character behavior, general AI-assisted tools, general level generation and complete game generation. The new scope for general general game AI beyond game-playing broadens the applicability and capacity of AI algorithms and our understanding of intelligence as tested in a creative domain that interweaves problem solving, art, and engineering.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] General Game Playing in AI Research and Education
    Thielscher, Michael
    KI 2011: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2011, 7006 : 26 - 37
  • [2] Optimising Level Generators for General Video Game AI
    Drageset, Olve
    Winands, Mark H. M.
    Gaina, Raluca D.
    Perez-Liebana, Diego
    2019 IEEE CONFERENCE ON GAMES (COG), 2019,
  • [3] General Video Game AI: Competition, Challenges, and Opportunities
    Perez-Liebana, Diego
    Samothrakis, Spyridon
    Togelius, Julian
    Lucas, Simon M.
    Schaul, Tom
    THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2016, : 4335 - 4337
  • [4] Deep Reinforcement Learning for General Video Game AI
    Tornado, Ruben Rodriguez
    Bontrager, Philip
    Togelius, Julian
    Liu, Jialin
    Perez-Liebana, Diego
    PROCEEDINGS OF THE 2018 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND GAMES (CIG'18), 2018, : 316 - 323
  • [5] General Board Game Playing for Education and Research in Generic AI Game Learning
    Konen, Wolfgang
    2019 IEEE CONFERENCE ON GAMES (COG), 2019,
  • [6] Self-Play for Training General Fighting Game AI
    Takano, Yoshina
    Inoue, Hideyasu
    Thawonmas, Ruck
    Harada, Tomohiro
    2019 NICOGRAPH INTERNATIONAL (NICOINT), 2019, : 120 - 120
  • [7] General Video Game AI: Learning from Screen Capture
    Kunanusont, Kamolwan
    Lucas, Simon M.
    Perez-Liebana, Diego
    2017 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2017, : 2078 - 2085
  • [8] Evolving Game Skill-Depth using General Video Game AI Agents
    Liu, Jialin
    Togelius, Julian
    Perez-Liebana, Diego
    Lucas, Simon M.
    2017 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2017, : 2299 - 2307
  • [9] Using a Team of General AI Algorithms to Assist Game Design and Testing
    Guerrero-Romero, Cristina
    Lucas, Simon M.
    Perez-Liebana, Diego
    PROCEEDINGS OF THE 2018 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND GAMES (CIG'18), 2018, : 466 - 473
  • [10] Developing a General Video Game AI Controller Based on an Evolutionary Approach
    Balabanov, Kristiyan
    Logofatu, Doina
    INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2019, PT I, 2019, 11431 : 315 - 326