Modeling and performance characterization of parameter estimation using perspective geometry
Modeling and performance characterization of parameter estimation using perspective geometry
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Artificial Intelligence
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Introduction to Reinforcement Learning
Exact and approximate algorithms for partially observable markov decision processes
Exact and approximate algorithms for partially observable markov decision processes
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The Knowledge Engineering Review
ICML '04 Proceedings of the twenty-first international conference on Machine learning
RFID-based techniques for human-activity detection
Communications of the ACM - Special issue: RFID
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Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Exploiting structure to efficiently solve large scale partially observable markov decision processes
Exploiting structure to efficiently solve large scale partially observable markov decision processes
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
International Journal of Robotics Research
Technological opportunities for supporting people with dementia who are living at home
International Journal of Human-Computer Studies
Logical Hierarchical Hidden Markov Models for Modeling User Activities
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
A decision-theoretic model of assistance
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A decision-theoretic approach to task assistance for persons with dementia
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Ubiquitous monitoring and user behaviour: A preliminary model
Journal of Ambient Intelligence and Smart Environments
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Journal of Ambient Intelligence and Smart Environments
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UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility
Rapid specification and automated generation of prompting systems to assist people with dementia
Pervasive and Mobile Computing
Simultaneous tracking and activity recognition (STAR) using many anonymous, binary sensors
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Journal of Ambient Intelligence and Smart Environments - Design and Deployment of Intelligent Environments
Ambient intelligence for quality of life assessment
Journal of Ambient Intelligence and Smart Environments - Ambient and Smart Component Technologies for Human Centric Computing
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This paper presents a model of interactive activity recognition and prompting for use in an assistive system for persons with cognitive disabilities. The system can determine the user's state by interpreting sensor data and/or by explicitly querying the user, and can prompt the user to begin, resume, or end tasks. The objective of the system is to help the user maintain a daily schedule of activities while minimizing interruptions from questions or prompts. The model is built upon an option-based hierarchical POMDP. Options can be programmed and customized to specify complex routines for prompting or questioning.The paper proposes a heuristic approach to solving the POMDP based on a dual control algorithm using selective-inquiry that can appeal for help from the user explicitly when the sensor data is ambiguous. The dual control algorithm is working effectively in the unified control model which features the adaptive option and robust state estimation. Simulation results show that the unified dual control model achieves the best performance and efficiency comparing with various alternatives. To further demonstrate the system's performance, lab experiments have been carried out with volunteer actors performing a series of carefully designed scenarios with different kinds of interruption cases. The results show that the system is able to successfully guide the agent through the sample schedule by delivering correct prompts while efficiently dealing with ambiguous situations.