General Video Game AI: A Multitrack Framework for Evaluating Agents, Games, and Content Generation Algorithms

Perez-Liebana, Diego1; Liu, Jialin2; Khalifa, Ahmed3; Gaina, Raluca D.1; Togelius, Julian3; Lucas, Simon M.1

2019-09

10.1109/TG.2019.2901021

IEEE Transactions on Games   影响因子和分区

2475-1502

2475-1510

General video game playing aims at designing an agent that is capable of playing multiple video games with no human intervention. In 2014, the General Video Game Artificial Intelligence (GVGAI) competition framework was created and released with the purpose of providing researchers a common open-source and easy-to-use platform for testing their artificial intelligence (AI) methods with potentially infinity of games created using the video game description language (VGDL). The framework has been expanded into several tracks during the last few years to meet the demands of different research directions. The agents are required either to play multiple unknown games with or without access to game simulations, or to design new game levels or rules. This survey paper presents the VGDL, the GVGAI framework, existing tracks, and reviews the wide use of GVGAI framework in research, education, and competitions five years after its birth. A future plan of framework improvements is also described.

Artificial intelligence computational intelligence games General Video Game AI (GVGAI) general video game playing (GVGP) video game description language (VGDL)

SCI ; EI

英语

通讯

Program for University Key Laboratory of Guangdong Province[2017KSYS008]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Software Engineering

WOS:000487066000002

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

20203209022639

Human computer interaction ; Interactive computer graphics

Artificial Intelligence:723.4 ; Computer Applications:723.5

Web of Science

1.Queen Mary Univ London, Dept Elect Engn & Comp Engn EECS, London E1 4NS, England
2.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen Key Lab Computat Intelligence, Univ Key Lab Evolving Intelligent Syst Guangdong, Shenzhen 518055, Peoples R China
3.NYU, Dept Comp Sci & Engn, New York, NY 11201 USA

Perez-Liebana, Diego,Liu, Jialin,Khalifa, Ahmed,et al. General Video Game AI: A Multitrack Framework for Evaluating Agents, Games, and Content Generation Algorithms[J]. IEEE Transactions on Games,2019,11(3):195-214.

Perez-Liebana, Diego,Liu, Jialin,Khalifa, Ahmed,Gaina, Raluca D.,Togelius, Julian,&Lucas, Simon M..(2019).General Video Game AI: A Multitrack Framework for Evaluating Agents, Games, and Content Generation Algorithms.IEEE Transactions on Games,11(3),195-214.

Perez-Liebana, Diego,et al."General Video Game AI: A Multitrack Framework for Evaluating Agents, Games, and Content Generation Algorithms".IEEE Transactions on Games 11.3(2019):195-214.