Integrating human and robot decision-making dynamics with feedback: Models and convergence analysis

— Leveraging research by psychologists on human decision-making, we present a human-robot decision-making problem associated with a complex task and study the corresponding joint decision-making dynamics. The collaborative task is designed so that the human makes decisions just as human subjects make decisions in the two-alternative, forcedchoice task, a well-studied decision-making task in behavioral experiments. The human subject chooses between two options at regular time intervals and receives a reward after each choice; for a variety of reward structures, the behavioral experiments show convergence to suboptimal choices. We propose a humansupervised robot foraging problem in which the human supervisor makes a sequence of binary decisions to assign the role of each robot in a group in response to a report from the robots on their resource return. We discuss conditions under which the decision dynamics of this human-robot task is reasonably well approximated by the kinds of reward...

• Type: Conference
• Year: 2008
• Where: CDC
• Authors: Ming Cao, Andrew Reed Stewart, Naomi Ehrich Leonard
• Keywords: CDC 2008, Control Systems, Human, Human Decision-making, Reward Structures