Plan, Activity, and Intent Recognition: Theory and Practice

Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning.

Plan, Activity, and Intent Recognition

explains the crucial role of these techniques in a wide variety of applications including:

• personal agent assistants
• computer and network security
• opponent modeling in games and simulation systems
• coordination in robots and software agents
• web e-commerce and collaborative filtering
• dialog modeling
• video surveillance
• smart homes

follow the history of this research area and witness exciting new developments in the field made possible by improved sensors, increased computational power, and new application areas.

• Combines basic theory on algorithms for plan/activity recognition along with results from recent workshops and seminars
• Explains how to interpret and recognize plans and activities from sensor data
• Provides valuable background knowledge and assembles key concepts into one guide for researchers or students studying these disciplines

Table of Contents

Part 1: Plan and GoalRecognition
Chapter 1 Hierarchical Goal Recognition
Chapter 2 Weighted Abduction for Discourse Processing Based on Integer Linear Programming
Chapter 3 Plan Recognition Using Statistical–Relational Models
Chapter 4 Keyhole Adversarial Plan Recognition for Recognition of Suspicious and Anomalous Behavior

Part 2: Activity Discovery and Recognition
Chapter 5 Stream Sequence Mining for Human Activity Discovery
Chapter 6 Learning Latent Activities from Social Signals with Hierarchical Dirichlet Processes

Part 3: Modeling Human Cognition
Chapter 7 Modeling Human Plan Recognition Using Bayesian Theory of Mind
Chapter 8 Decision-Theoretic Planning in Multiagent Settings with Application to Behavioral Modeling

Part 4: Multiagent Systems
Chapter 9 Multiagent Plan Recognition from Partially Observed Team Traces
Chapter 10 Role-Based Ad Hoc Teamwork

Part 5: Applications
Chapter 11 Probabilistic Plan Recognition for Proactive Assistant Agents
Chapter 12 Recognizing Player Goals in Open-Ended Digital Games with Markov Logic Networks
Chapter 13 Using Opponent Modeling to Adapt Team Play in American Football
Chapter 14 Intent Recognition for Human–Robot Interaction