Plan, Activity, and Intent Recognition

1st Edition

Theory and Practice

Print ISBN: 9780123985323
eBook ISBN: 9780124017108
Imprint: Morgan Kaufmann
Published Date: 24th February 2014
Page Count: 424
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72.99 + applicable tax
119.95 + applicable tax
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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.

Key Features

  • 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


Academic researchers and industrial researchers in specific application areas such as user interface design and video surveillance systems.

Table of Contents

About the Editors




1: Plan and Goal Recognition

1: Hierarchical Goal Recognition

1.1 Introduction

1.2 Previous Work

1.3 Data for Plan Recognition

1.4 Metrics for Plan Recognition

1.5 Hierarchical Goal Recognition

1.6 System Evaluation

1.7 Conclusion

2: Weighted Abduction for Discourse Processing Based on Integer Linear Programming

2.1 Introduction

2.2 Related Work

2.3 Weighted Abduction

2.4 ILP-based Weighted Abduction

2.5 Weighted Abduction for Plan Recognition

2.6 Weighted Abduction for Discourse Processing

2.7 Evaluation on Recognizing Textual Entailment

2.8 Conclusion

3: Plan Recognition Using Statistical–Relational Models

3.1 Introduction

3.2 Background

3.3 Adapting Bayesian Logic Programs

3.4 Adapting Markov Logic

3.5 Experimental Evaluation

3.6 Future Work

3.7 Conclusion

4: Keyhole Adversarial Plan Recognition for Recognition of Suspicious and Anomalous Behavior

4.1 Introduction

4.2 Background: Adversarial Plan Recognition

4.3 An Efficient Hybrid System for Adversarial Plan Recognition

4.4 Experiments to Detect Anomalous and Suspicious Behavior

4.5 Future Directions and Final Remarks

2: Activity Discovery and Recognition

5: Stream Sequence Mining for Human Activity Discovery

5.1 Introduction

5.2 Related Work

5.3 Proposed Model

5.4 Experiments

5.5 Conclusion

6: Learning Latent Activities from Social Signals with Hierarchical Dirichlet Processes

6.1 Introduction

6.2 Related Work

6.3 Bayesian Nonparametric Approach to Inferring Latent Activities

6.4 Experiments

6.5 Conclusion

3: Modeling Human Cognition

7: Modeling Human Plan Recognit


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© Morgan Kaufmann 2014
Morgan Kaufmann
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"This book serves to provide a coherent snapshot of the exciting developments in the field enabled by improved sensors, increased computational power, and new application areas." -, August 2014


"Plan recognition, activity recognition, and intent recognition all involve making inferences about other actors from observations of their behavior. These inferences are crucial in a wide range of applications including intelligent assistants, computer security, and dialogue management systems. This volume, edited by leading researchers, provides a timely snapshot of some of the key formulations, techniques, and applications that have been developed in this rich and rapidly evolving field."

–Dr. Hector Geffner, ICREA & Universitat Pompeu Fabra, Barcelona

"This book collects some of the top senior people in the field of plan recognition with some of the newest researchers. It offers a comprehensive review of plan recognition from multiple viewpoints, encompassing both logical and probabilistic formalisms and covering mathematical theory, computer science applications, and human cognitive models."

–Dr. Peter Norvig, Director of Research at Google Inc.

"Plan, Activity, and Intent Recognition is an indispensable resource for creating systems that infer peoples’ goals and plans on the basis of their behavior. Researchers in security, natural language dialog systems, smart spaces and pervasive computing, and other areas will find a comprehensive and up to date survey of methods, applications, and open research challenges."

–Dr. Henry Kautz, University of Rochester, Past President of AAAI (Association for the Advancement of Artificial Intelligence)