Team Plan Recognition: A Review of the State of the Art
It addresses the problem of assisting groups of humans in coordinated tasks, but is incremental as it is a review paper.
This article reviews the state of the art in team plan recognition, focusing on logic-based approaches to help AI systems understand coordinated human tasks, but does not present new experimental results or concrete numbers.
There is an increasing need to develop artificial intelligence systems that assist groups of humans working on coordinated tasks. These systems must recognize and understand the plans and relationships between actions for a team of humans working toward a common objective. This article reviews the literature on team plan recognition and surveys the most recent logic-based approaches for implementing it. First, we provide some background knowledge, including a general definition of plan recognition in a team setting and a discussion of implementation challenges. Next, we explain our reasoning for focusing on logic-based methods. Finally, we survey recent approaches from two primary classes of logic-based methods (plan library-based and domain theory-based). We aim to bring more attention to this sparse but vital topic and inspire new directions for implementing team plan recognition.