This study tested the capability of artificial social intelligence to make inferences and predictions concerning the state and behaviors of 3-person teams executing an urban search and rescue task in Minecraft.

The ASIST Study-2 dataset was developed in a human subjects research study designed to assess the capability of artificial intelligence to infer the state and predict the actions of members of a three-person team executing an urban search and rescue task in Minecraft. The data were developed under Contract No. HR001119C0130 to the Defense Advanced Research Projects Agency (DARPA). The dataset comprises approximately 2,100 files and 300GB of data. We have partitioned the full dataset into folders that support research in specific areas. Thus, researchers can more easily download only the files of value to them.
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Artificial Social Intelligence for Successful Teams (ASIST) Study 1 Falcon Testbed Dataset
Artificial Social Intelligence for Successful Teams (ASIST) Study 1 Falcon Testbed Dataset
Aug 18, 2025
Lixiao Huang; Jared Freeman; Nancy Cooke, 2025, "Artificial Social Intelligence for Successful Teams (ASIST) Study 1 Falcon Testbed Dataset", https://doi.org/10.48349/ASU/1CY5AR, ASU Library Research Data Repository, V1, UNF:6:Moq9o4psJTgh9X5zzFwDbA== [fileUNF]
Artificial Social Intelligence for Successful Teams (ASIST) has a total of 4 studies, with a program overview on this website:https://artificialsocialintelligence.org/ ASIST consists of 13 institutions and more than 300 individual contributors. Arizona State University (ASU) and Aptima as TA3 jointly developed the testbed, integrated requests from...
Artificial Social Intelligence for Successful Teams (ASIST) Study 4 Dragon Testbed Dataset
Feb 7, 2024
Lixiao Huang; Adam Fouse; Nancy Cooke; Edward Weiss, 2024, "Artificial Social Intelligence for Successful Teams (ASIST) Study 4 Dragon Testbed Dataset", https://doi.org/10.48349/ASU/ZO6XVR, ASU Library Research Data Repository, V2, UNF:6:jkhVIRagnIe25M/7ClVYUg== [fileUNF]
Artificial Social Intelligence for Successful Teams (ASIST) Study 4 Dragon Testbed Dataset was developed in a human subjects research study designed to assess the capability of artificial intelligence to instantiate a Machine Theory of Teams and apply it to generate and issue (or withhold) advice to team members that improve team state (e.g., motiv...
Artificial Social Intelligence for Successful Teams (ASIST) Study 3
Jan 3, 2023
Lixiao Huang; Jared Freeman; Nancy Cooke; John “JCR” Colonna-Romano; Matt Wood; Verica Buchanan; Stephen Caufman, 2022, "Artificial Social Intelligence for Successful Teams (ASIST) Study 3", https://doi.org/10.48349/ASU/QDQ4MH, ASU Library Research Data Repository, V3, UNF:6:M0oVzTeD5aBRBm/AbSdJ/g== [fileUNF]
The ASIST Study-3 dataset was developed in a human subjects research study designed to assess the capability of artificial intelligence to instantiate a Machine Theory of Teams, and apply it to generate and issue (or withold) advice to team members that improve team state (e.g., motivation), process (e.g., synchronization), and mission effects (e.g...
Artificial Social Intelligence for Successful Teams (ASIST) Study 2
May 26, 2022
Lixiao Huang; Jared Freeman; Nancy Cooke; Samantha Dubrow; John “JCR” Colonna-Romano; Matt Wood; Verica Buchanan; Stephen Caufman; Xiaoyun Yin, 2022, "Artificial Social Intelligence for Successful Teams (ASIST) Study 2", https://doi.org/10.48349/ASU/BZUZDE, ASU Library Research Data Repository, V4, UNF:6:OJ3XctVE31iBZs09zhPpFQ== [fileUNF]
The ASIST Study-2 dataset was developed in a human subjects research study designed to assess the capability of artificial intelligence to infer the state and predict the actions of members of a three-person team executing an urban search and rescue task in Minecraft. The data were developed under Contract No. HR001119C0130 to the Defense Advanced...
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