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Research Projects

Trust Network Emergence Amongst Resource-Constrained Human-Agent Teams

Enabling AI agent teams to care and be 'socially'-aware

Sponsor: DEVCOM Army Research Lab (ARL) via STRONG (Strengthening Teamwork for Robust Operations in Novel Groups) Collaborative Research Alliance (CRA)

Senior investigators: Kshitij Jerath, Paul Robinette, and Reza Ahmadzadeh

Junior investigators: Alden Daniels, Akshay Kolli, Hossein Haeri, Zahra Rezaei Khavas, Yasin Findik, Hamid Osooli, Alok Malik, Monish Kotturu, Huy Huynh, Kalvin McCallum, Nathan Uhunsere, Mike Fisher, Ashwin Nair

Teams succeed because of the network of relationships they possess, and the emergent behaviors this network facilitates. These emergent behaviors arise due to three constructs: (a) multiple agents in the team capable of taking actions, (b) interactions between the agents, and (c) emergence of global-scale patterns due to the interactions. The overall research strategy and objective tackles each of these constructs as separate tasks in the context of a search and rescue mission. Search and rescue operations are often severely resource constrained in terms of time, energy, and information organization. Operating in such resource-constrained scenarios can impact the ability of human-agent teams to tackle complex problems, resulting in sub-optimal outputs. In this project, we have been studying this problem from three aspects: how team network structures affect performance in search and rescue, how multiple agents can learn together, and how humans trust the search-and-rescue agents. Our work has shown that resource-constrained teams prefer structures that are more self-oriented. Similarly, we found that specific network structures can guide learning agents to more prosocial behaviors.
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