Speculative Game Design of Asymmetric Cooperative Games to Study Human-Machine Teaming
Authors: 
Erik Harpstead, 
Kimberly Stowers, Lane Lawley, Qiao Zhang, Christopher MaclellanAuthors Info & Claims
Article No.: 77, Pages 1 - 4
Abstract
While recent advances in Artificial Intelligence and Machine Learning have demonstrated the potential for AI systems to outperform human experts in many domains, including games, AI systems still generally lack the ability to team with humans on complex tasks. One of the barriers to addressing this challenge is a lack of shared task domains in which to do basic research to study Human-Machine Teaming strategies. In our work, we employ speculative game design to create asymmetric cooperative games that can serve as test beds to study human-machine teaming challenges. In this paper, we will describe our general approach and detail the current state of our development efforts.
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April 2023
621 pages
Copyright © 2023 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
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Association for Computing Machinery
New York, NY, United States
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Published: 12 April 2023
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FDG 2023
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