TASC: Teammate Algorithm for Shared Cooperation

For robots to be perceived as full-fledged team members, they must display intelligent behavior along multiple dimensions. One challenge is that even when the robot and human are on the same team, the interaction may not feel like teamwork to the human. We present a novel algorithm, Teammate Algorithm for Shared Cooperation (TASC). TASC is motivated by the concept of shared cooperative activity (SCA) for human-human teamwork, developed in prior work by Bratman. We focus on enabling the robot to prioritize certain SCA facets in its action selection depending on the task. We evaluated TASC in three experiments using different tasks with human users on Amazon Mechanical Turk. Our results show that TASC enabled participants to predict the robot’s goal earlier by one robot move and with greater confidence. The robot also helped reduce participants’ energy usage in a simulated block-moving task. Altogether, these results show that considering the SCA facets in the robot’s action selection improves teamwork.

Authors

• Mai Lee Chang
• Taylor Kessler Faulkner
• Thomas Benjamin Wei
• Elaine Schaertl Short
• Gokul Anandaraman
• Andrea Thomaz

Keywords

• Prediction algorithms
• Teamwork
• Task analysis
• Robots
• Intelligent robots
• Team Sports
• Team Members
• Human Users
• Simulated Task
• Changes In Values
• Objective Measures
• Data Pre-processing
• Test Session
• User Study
• Time Task
• Correct Predictions
• Equal Status
• Goal State
• Team Performance
• Reward Function
• Markov Decision Process
• Description Task
• Navigation Task
• Weight Setting
• Average Reward
• Levels Of Exhaustion
• Different Types Of Tasks