Andrea Nedic

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To investigate the influence of input from fellow group members in a constrained decision-making context, we consider a game in which subjects freely select one of two options (A or B), and are informed of the reward resulting from that choice following each trial. Rewards are computed based on the fraction x of past A choices by two functions fA(x), fB(x)(More)
| To investigate the influence of information about fellow group members in a constrained decision-making context, we develop four two-armed bandit tasks in which subjects freely select one of two options (A or B) and are informed of the resulting reward following each choice. Rewards are determined by the fraction x of past A choices by two functions(More)
With a principled methodology for systematic design of human-robot decision-making teams as a motivating goal, we seek an analytic, model-based description of the influence of team and network design parameters on decision-making performance. Given that there are few reliably predictive models of human decision making, we consider the relatively well(More)
The mechanisms that govern human learning and decision making under uncertainty have been the focus of intense behavioral and, more recently, neuroscientific investigation. Substantial progress has been made in building models of the processes involved, and identifying underlying neural mechanisms using simple, two-alternative forced choice decision tasks.(More)
Decades of research have established that decision-making is dramatically impacted by both the rewards an individual receives and the behavior of others. How do these distinct influences exert their influence on an individual's actions, and can the resulting behavior be effectively captured in a computational model? To address this question, we employed a(More)
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