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First-Person Shooter Game for Virtual Reality Headset with Advanced Multi-Agent Intelligent System

Published: 01 October 2016 Publication History

Abstract

We present a multiplayer first-person shooter (FPS) game with advanced intelligent non-playable characters (NPC) under computer control. The game is specially adapted for playing in VR headset so the simulator sickness symptoms are significantly reduced. The demo allows users to play with the other human and NPC players in a shooter game made in Unreal Engine 4. User can verify his/her game skills versus evolving human-like NPCs with a level adjusting model. The humanness of NPC was verified with Alan Turing game test beating 52% record from BotPrize'12 competition.

Supplementary Material

ZIP File (de475.zip)
de475-makarov-presentation.pdf - presentation of technical demo program. de475-makarov-booth-configuration.pdf - hardware/software minimum requirements for booth configuration.

References

[1]
P. J. C. Adachi and T. Willoughby. More than just fun and games: The longitudinal relationships between strategic video games, self-reported problem solving skills, and academic grades. Journal of Youth and Adolescence, 42(7):1041--1052, 2013.
[2]
I. Granic, A. Lobel, and R. C. Engels. The benefits of playing video games. American Psychologist, 69(1):66--78, 2014.
[3]
I. V. Karpov, J. Schrum, and R. Miikkulainen. Believable Bots: Can Computers Play Like People?, chapter Believable Bot Navigation via Playback of Human Traces, pages 151--170. Springer Berlin Heidelberg, Berlin, Heidelberg, 2012.
[4]
I. Makarov, M. Tokmakov, and L. Tokmakova. Imitation of human behavior in 3D-shooter game. In 4th International Conference on Analysis of Images, Social Networks and Texts, pages 64--77, 2015.
[5]
M. Smith, S. Lee-Urban, and H. M. noz Avila. Retaliate: Learning winning policies in first-person shooter games. In Proceedings of the 19th National Conference on Innovative Applications of Artificial Intelligence - Volume 2, IAAI'07, pages 1801--1806. AAAI Press, 2007.
[6]
D. Wang and A. H. Tan. Creating autonomous adaptive agents in a real-time first-person shooter computer game. IEEE Transactions on Computational Intelligence and AI in Games, 7(2):123--138, June 2015.

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Information & Contributors

Information

Published In

cover image ACM Conferences
MM '16: Proceedings of the 24th ACM international conference on Multimedia
October 2016
1542 pages
ISBN:9781450336031
DOI:10.1145/2964284
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 October 2016

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Author Tags

  1. first-person shooter
  2. game artificial intelligence
  3. reinforcement learning
  4. unreal engine
  5. virtual reality

Qualifiers

  • Demonstration

Conference

MM '16
Sponsor:
MM '16: ACM Multimedia Conference
October 15 - 19, 2016
Amsterdam, The Netherlands

Acceptance Rates

MM '16 Paper Acceptance Rate 52 of 237 submissions, 22%;
Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

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  • (2024)Tangram-Splatting: Optimizing 3D Gaussian Splatting Through Tangram-inspired Shape PriorsProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680688(3075-3083)Online publication date: 28-Oct-2024
  • (2024)Graph Neural Networks for Complex Fluid Simulations2024 IEEE 28th International Conference on Intelligent Engineering Systems (INES)10.1109/INES63318.2024.10629094(000145-000152)Online publication date: 17-Jul-2024
  • (2024)Inpainting Semantic and Depth Features to Improve Visual Place Recognition in the WildIEEE Access10.1109/ACCESS.2024.335003812(5163-5176)Online publication date: 2024
  • (2024)Gesture Recognition on Video DataRecent Trends in Analysis of Images, Social Networks and Texts10.1007/978-3-031-67008-4_14(180-193)Online publication date: 30-Jul-2024
  • (2023)Financial Trading via Reinforcement Learning and Convolutional Neural Networks2023 IEEE 21st Jubilee International Symposium on Intelligent Systems and Informatics (SISY)10.1109/SISY60376.2023.10417967(000091-000096)Online publication date: 21-Sep-2023
  • (2023)Dealing With Sparse Rewards Using Graph Neural NetworksIEEE Access10.1109/ACCESS.2023.330592711(89180-89187)Online publication date: 2023
  • (2022)Implementation of the Racing Game with the Virtual Reality and Cable Suspended Parallel Robot (CSPR)2022 22nd International Conference on Control, Automation and Systems (ICCAS)10.23919/ICCAS55662.2022.10003804(288-291)Online publication date: 27-Nov-2022
  • (2022)Multi-Modal Deep Reinforcement Learning in ViZDoom with Audio Component2022 IEEE 20th Jubilee International Symposium on Intelligent Systems and Informatics (SISY)10.1109/SISY56759.2022.10036289(000437-000442)Online publication date: 15-Sep-2022
  • (2022)Transformer-Based Deep Reinforcement Learning in VizDoomRecent Trends in Analysis of Images, Social Networks and Texts10.1007/978-3-031-15168-2_9(96-110)Online publication date: 30-Aug-2022
  • (2021)On the Synergy between Virtual Reality and Multi-Agent SystemsSustainability10.3390/su1308432613:8(4326)Online publication date: 13-Apr-2021
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