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. 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 Content: Plan, Activity, and Intent Recognition , Page i Plan, Activity, and Intent Recognition , Page iii Copyright , Page iv About the Editors , Page xi List of Contributors , Pages xiii-xv Preface , Pages xvii-xviii Introduction , Pages xix-xxxv Chapter 1 - Hierarchical Goal Recognition , Pages 3-32 , Nate Blaylock, James Allen Chapter 2 - Weighted Abduction for Discourse Processing Based on Integer Linear Programming , Pages 33-55 , Naoya Inoue, Ekaterina Ovchinnikova, Kentaro Inui, Jerry Hobbs Chapter 3 - Plan Recognition Using Statistical–Relational Models , Pages 57-85 , Sindhu Raghavan, Parag Singla, Raymond J. Mooney Chapter 4 - Keyhole Adversarial Plan Recognition for Recognition of Suspicious and Anomalous Behavior , Pages 87-119 , Dorit Avrahami-Zilberbrand, Gal A. Kaminka Chapter 5 - Stream Sequence Mining for Human Activity Discovery , Pages 123-148 , Parisa Rashidi Chapter 6 - Learning Latent Activities from Social Signals with Hierarchical Dirichlet Processes , Pages 149-174 , Dinh Phung, Thuong Nguyen, Sunil Gupta, Svetha Venkatesh Chapter 7 - Modeling Human Plan Recognition Using Bayesian Theory of Mind , Pages 177-204 , Chris L. Baker, Joshua B. Tenenbaum Chapter 8 - Decision-Theoretic Planning in Multiagent Settings with Application to Behavioral Modeling , Pages 205-224 , Prashant Doshi, Xia Qu, Adam Goodie Chapter 9 - Multiagent Plan Recognition from Partially Observed Team Traces , Pages 227-249 , Hankz Hankui Zhuo Chapter 10 - Role-Based Ad Hoc Teamwork , Pages 251-272 , Katie Genter, Noa Agmon, Peter Stone Chapter 11 - Probabilistic Plan Recognition for Proactive Assistant Agents , Pages 275-288 , Jean Oh, Felipe Meneguzzi, Katia Sycara Chapter 12 - Recognizing Player Goals in Open-Ended Digital Games with Markov Logic Networks , Pages 289-311 , Eun Y. Ha, Jonathan P. Rowe, Bradford W. Mott, James C. Lester Chapter 13 - Using Opponent Modeling to Adapt Team Play in American Football , Pages 313-341 , Kennard R. Laviers, Gita Sukthankar Chapter 14 - Intent Recognition for Human–Robot Interaction , Pages 343-365 , Richard Kelley, Alireza Tavakkoli, Christopher King, Amol Ambardekar, Liesl Wigand, Monica Nicolescu, Mircea Nicolescu Author Index , Pages 367-378 Subject Index , Pages 379-385
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.
- 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
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. * 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
