Plan, Activity, and Intent Recognition: Theory and Practice
- Length: 424 pages
- Edition: 1
- Language: English
- Publisher: Morgan Kaufmann
- Publication Date: 2014-03-10
- ISBN-10: 0123985323
- ISBN-13: 9780123985323
- Sales Rank: #3351396 (See Top 100 Books)
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