Plan, activity, and intent recognition : theory and practice
著者
書誌事項
Plan, activity, and intent recognition : theory and practice
Elsevier, c2014
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注記
Other editors:Robert P. Goldman, Christopher Geib, David V. Pynadath, Hung Hai Bui
Includes bibliographical references and index
内容説明・目次
内容説明
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
In this book, 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.
目次
Plan and Goal Recognition 1. Hierarchical Goal Recognition 2. Weighted Abduction for Discourse Processing Based on Integer Linear Programming 3. Plan Recognition using Statistical Relational Models 4. Keyhole Adversarial Plan Recognition for Recognition of Suspicious and Anomalous Behavior
Activity Discovery and Recognition 5. Scaling Activity Recognition 6. Extraction of Latent Patterns and Contexts from Social Honest Signals Using Hierarchical Dirichlet Processes
Modeling Human Cognition 7. Modeling Human Plan Recognition using Bayesian Theory of Mind 8. Decision Theoretic Planning in Multiagent Settings with Application to Modeling Human Strategic Behavior
Multiagent Systems 9. Multiagent Plan Recognition from Partially Observed Team Traces 10. Role-based Ad Hoc Teamwork
Applications 11. Probabilistic plan recognition for proactive assistant agents 12. Recognizing Player Goals in Open-Ended Digital Games with Markov Logic Networks 13. Using Opponent Modeling to Adapt Team Play in American Football 14. Intent Recognition for Human-Robot Interaction
「Nielsen BookData」 より
