Plan, Activity, and Intent Recognition
Papers from the AAAI Workshop
Christopher Geib and David Pynadath, Cochairs
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 multiagent 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, observation-based coordination in robots and software agents, and e-commerce and collaborative filtering.
This widespread diversity of applications and disciplines, while producing a wealth of ideas and results, has unfortunately contributed to fragmentation in the field, as researchers publish relevant results in a wide spectrum of journals and conferences. This workshop sought to bring together researchers and practitioners from diverse backgrounds, to share in ideas and recent results. It's goal was to to identify important research directions and opportunities for synthesis and unification.