Plan recognition, activity recognition, and intent recognition all involve making inferences about other actors from observations of their behavior, i.e., their interaction with the environment and with each other. The observed actors may be software agents, robots, or humans. This synergistic area of research combines and unifies techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. It plays a crucial role in a wide variety of applications including: assistive technology, software assistants, computer and network security, behavior recognition, coordination in robots and software agents, and more.

This workshop seeks to bring together researchers and practitioners from diverse backgrounds, to share in ideas and recent results. It will aim to identify important research directions, opportunities for synthesis and unification of representations and algorithms for plan recognition. This year's workshop will be centered on application domains. This will include a focused discussion where we will present compare the various representations common in the literature and applications. We believe this will work to help identify areas of synergy between different communities and to provide opportunities and incentives for future work.