382 citations · 896 across the 14 of their papers we have counts for
11 papers · 1 filter
TRIBE: Predicting Team Performance via Communication Behavior Ensembles
Ali Jalal-Kamali, Nikolos Gurney, David V. Pynadath +1
Designing autonomous agents that effectively assist human teams hinges on understanding team dynamics, often without task specific knowledge. We present TRIBE, a domain independent…
Predicting Team Performance from Communications in Simulated Search-and-Rescue
Ali Jalal-Kamali, Nikolos Gurney, David Pynadath
Understanding how individual traits influence team performance is valuable, but these traits are not always directly observable. Prior research has inferred traits like trust from…
Operational Collective Intelligence of Humans and Machines
Nikolos Gurney, Fred Morstatter, David V. Pynadath +2
We explore the use of aggregative crowdsourced forecasting (ACF) as a mechanism to help operationalize ``collective intelligence'' of human-machine teams for coordinated actions. W…
Spontaneous Theory of Mind for Artificial Intelligence
Nikolos Gurney, David V. Pynadath, Volkan Ustun
Existing approaches to Theory of Mind (ToM) in Artificial Intelligence (AI) overemphasize prompted, or cue-based, ToM, which may limit our collective ability to develop Artificial…
Multiagent Inverse Reinforcement Learning via Theory of Mind Reasoning
Haochen Wu, Pedro Sequeira, David V. Pynadath
We approach the problem of understanding how people interact with each other in collaborative settings, especially when individuals know little about their teammates, via Multiagen…
The Role of Heuristics and Biases During Complex Choices with an AI Teammate
Nikolos Gurney, John H. Miller, David V. Pynadath
Behavioral scientists have classically documented aversion to algorithmic decision aids, from simple linear models to AI. Sentiment, however, is changing and possibly accelerating…