Intent integration for human‐agent teaming. Issue 4 (5th April 2022) - Schneider, Michael F.; Miller, Michael E.; Ford, Thomas C.; Peterson, Gilbert; Jacques, David
Abstract: Knowledge of intent is critical in high performing human teams. The fundamental question addressed by this research is, how should intent be integrated into future human‐artificial agent (AA) teams to improve coordination among team members? A brief review of the use of intent for improving performance within human‐human teams is conducted to provide a better understanding of this term. This review differentiates intent estimation from intent application, as well as the differentiation of "why, " "what" and "how" based intent. A taxonomy of intent‐based systems is then developed through a review of existing examples in the literature. Together these reviews demonstrate that intent has been modeled in a variety of ways without a cohesive understanding of intent and its different forms. Based upon these reviews and our understanding of multi‐agent system architectures, we propose "operationalized intent" as a method of modeling intent regarding "how" the operators would like to execute the team's tasks. We propose including an Intent Agent (IA) dedicated to estimating intent of each operator and embedding knowledge of how to execute within the Functional Agents (FAs) of a multi‐agent system. The proposed Operationalized Intent Ontology provides a means of modeling human‐agent teams as an intent informed system.