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Evaluating artificial social intelligence in an urban search and rescue task environment

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Human team members show a remarkable ability to infer the state of their partners and anticipate their needs and actions. Prior research demonstrates that an artificial system can make some predictions accurately concerning artificial agents. This study investigated whether an artificial system could generate a robust Theory of Mind of…

Human team members show a remarkable ability to infer the state of their partners and anticipate their needs and actions. Prior research demonstrates that an artificial system can make some predictions accurately concerning artificial agents. This study investigated whether an artificial system could generate a robust Theory of Mind of human teammates. An urban search and rescue (USAR) task environment was developed to elicit human teamwork and evaluate inference and prediction about team members by software agents and humans. The task varied team members’ roles and skills, types of task synchronization and interdependence, task risk and reward, completeness of mission planning, and information asymmetry. The task was implemented in MinecraftTM and applied in a study of 64 teams, each with three remotely distributed members. An evaluation of six Artificial Social Intelligences (ASI) and several human observers addressed the accuracy with which each predicted team performance, inferred experimentally manipulated knowledge of team members, and predicted member actions. All agents performed above chance; humans slightly outperformed ASI agents on some tasks and significantly outperformed ASI agents on others; no one ASI agent reliably outperformed the others; and the accuracy of ASI agents and human observers improved rapidly though modestly during the brief trials.
ContributorsFreeman, Jared T. (Author) / Huang, Lixiao (Author) / Woods, Matt (Author) / Cauffman, Stephen J. (Author)
Created2021-11-04
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A Study to Evaluate Urban Heat Mitigation Design Strategies to Improve Pedestrian’s Thermal Perception in Existing Canyons of Extreme Hot-Arid Cities. The Case of Phoenix, Arizona

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The rapid rate of urbanization coupled with continued population growth and anthropogenic activities has resulted in a myriad of urban climate related impacts across different cities around the world. Hot-arid cities are more vulnerable to induced urban heat effects due to the intense solar radiation during most of the year,…

The rapid rate of urbanization coupled with continued population growth and anthropogenic activities has resulted in a myriad of urban climate related impacts across different cities around the world. Hot-arid cities are more vulnerable to induced urban heat effects due to the intense solar radiation during most of the year, leading to increased ambient air temperature and outdoor/indoor discomfort in Phoenix, Arizona. With the fast growth of the capital city of Arizona, the automobile-dependent planning of the city contributed negatively to the outdoor thermal comfort and to the people's daily social lives. One of the biggest challenges for hot-arid cities is to mitigate against the induced urban heat increase and improve the outdoor thermal. The objective of this study is to propose a pragmatic and useful framework that would improve the outdoor thermal comfort, by being able to evaluate and select minimally invasive urban heat mitigation strategies that could be applied to the existing urban settings in the hot-arid area of Phoenix. The study started with an evaluation of existing microclimate conditions by means of multiple field observations cross a North-South oriented urban block of buildings within Arizona State University’s Downtown campus in Phoenix. The collected data was evaluated and analyzed for a better understanding of the different local climates within the study area, then used to evaluate and partially validate a computational fluid dynamics model, ENVI-Met. Furthermore, three mitigation strategies were analyzed to the Urban Canopy Layer (UCL) level, an increase in the fraction of permeable materials in the ground surface, adding different configurations of high/low Leaf Area Density (LAD) trees, and replacing the trees configurations with fabric shading. All the strategies were compared and analyzed to determine the most impactful and effective mitigation strategies. The evaluated strategies have shown a substantial cooling effect from the High LAD trees scenarios. Also, the fabric shading strategies have shown a higher cooling effect than the Low LAD trees. Integrating the trees scenarios with the fabric shading had close cooling effect results in the High LAD trees scenarios. Finally, how to integrate these successful strategies into practical situations was addressed.
ContributorsAldakheelallah, Abdullah (Author) / Reddy, T Agami (Thesis advisor) / Middel, Ariane (Committee member) / Coseo, Paul (Committee member) / Arizona State University (Publisher)
Created2020