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
observation-based coordination in robots and software agents
e-commerce and collaborative filtering

This wide-spread 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 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 and to identify opportunities for synthesis and unification. The workshop will especially emphasize a discussion of challenges and trends: Reasoning with incomplete or incorrect knowledge of others, learning activity and behavioral models from interaction and observations, agent modeling on the web and in open multi-agent systems, modeling multiple agents and the interactions between them, inferring the capabilities of agents from observations, and using agent modeling for coordination and teamwork.

Topics

Contributions are sought in the following areas of research:

Plan, activity, intent, or behavior recognition
Adversarial planning, opponent modeling
Modeling multiple agents, modeling teams
User modeling on the web and in intelligent user interfaces
Acquaintance models
Plan recognition and user modeling in marketplaces and e-commerce
Intelligent tutoring systems (ITS)
Machine learning for plan recognition and user modeling
Personal software assistants
Social network learning and analysis
Monitoring agent conversations (overhearing)
Observation-based coordination and collaboration (teamwork)
Multi-agent plan recognition
Observation-based failure detection
Uncertainty reasoning for plan recognition
Representations for agent modeling
Modeling social interactions
Inferring emotional states
Reverse engineering and program recognition
Programming by demonstration
Imitation
Due to the diversity of disciplines engaging in this area, related contributions in other fields, are also welcome.
Format

The workshop will be split 50/50 between a series of research presentations, organized into topical sessions (topics to be decided based on submissions) and two interdisciplinary panels 1) seeking to highlight research contributions and challenges unifying the different sub-areas, and 2) to discuss the relevance of multiple approaches to different sub-areas to better understand the actual differences between the sub-areas and problems needing more focus.
Submission

We welcome submissions describing either relevant work or proposals for discussion topics that will be of interest to the workshop. Submissions are accepted in PDF format only, using the IJCAI formatting guidelines. Submissions must be no longer than eight pages in length, including references and figures.

Please e-mail submissions to cgeib@inf.ed.ac.uk.