General Framework for the Optimization of the Human-Robot Collaboration Decision-Making Process Through the Ability to Change Performance Metrics.

This paper proposes a new decision-making framework in the context of Human-Robot Collaboration (HRC). State-of-the-art techniques consider the HRC as an optimization problem in which the utility function, also called reward function, is defined to accomplish the task regardless of how well the interaction is performed. When the performance metrics are considered, they cannot be easily changed within the same framework.