Evidential reasoning using stochastic simulation of causal models
Artificial Intelligence
Operations Research
Probabilistic reasoning in intelligent systems: networks of plausible inference
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Intention is choice with commitment
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Computational Intelligence
Dynamic network models for forecasting
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UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Use of the Gibbs sampler in expert systems
Artificial Intelligence
The data association problem when monitoring robot vehicles using dynamic belief networks
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Approximating probabilistic inference in Bayesian belief networks is NP-hard
Artificial Intelligence
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Artificial Intelligence
The automated mapping of plans for plan recognition
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Factorial Hidden Markov Models
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Reinforcement learning with hierarchies of machines
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Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning
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An Introduction to Variational Methods for Graphical Models
Machine Learning
Stochastic dynamic programming with factored representations
Artificial Intelligence
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Expert Systems and Probabiistic Network Models
Expert Systems and Probabiistic Network Models
Bayesian Models for Keyhole Plan Recognition in an Adventure Game
User Modeling and User-Adapted Interaction
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Simulation Approaches to General Probabilistic Inference on Belief Networks
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Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
On the Recognition of Abstract Markov Policies
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Hybrid Propagation in Junction Trees
IPMU'94 Selected papers from the 5th International Conference on Processing and Management of Uncertainty in Knowledge-Based Systems, Advances in Intelligent Computing
Probabilistic State-Dependent Grammars for Plan Recognition
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Hierarchical control and learning for markov decision processes
Hierarchical control and learning for markov decision processes
Probabilistic grammars for plan recognition
Probabilistic grammars for plan recognition
Decomposition techniques for planning in stochastic domains
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A new model of plan recognition
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Tractable inference for complex stochastic processes
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Hierarchical solution of Markov decision processes using macro-actions
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Stochastic simulation algorithms for dynamic probabilistic networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Accounting for context in plan recognition, with application to traffic monitoring
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Recognition of Human Activity through Hierarchical Stochastic Learning
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning to Communicate and Act Using Hierarchical Reinforcement Learning
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Journal of Intelligent and Robotic Systems
Robot introspection through learned hidden Markov models
Artificial Intelligence
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
ICML '06 Proceedings of the 23rd international conference on Machine learning
Multi-modal emotive computing in a smart house environment
Pervasive and Mobile Computing
Learning and inferring transportation routines
Artificial Intelligence
The Journal of Machine Learning Research
Robust recognition and segmentation of human actions using HMMs with missing observations
EURASIP Journal on Applied Signal Processing
Activity recognition via user-trace segmentation
ACM Transactions on Sensor Networks (TOSN)
Intentional motion on-line learning and prediction
Machine Vision and Applications
Logical Hierarchical Hidden Markov Models for Modeling User Activities
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Hierarchical group process representation in multi-agent activity recognition
Image Communication
Navigational strategies in behaviour modelling
Artificial Intelligence
Learning Discriminative Sequence Models from Partially Labelled Data for Activity Recognition
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Efficient duration and hierarchical modeling for human activity recognition
Artificial Intelligence
Plan recognition for interface agents
Artificial Intelligence Review
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Artificial Intelligence
An Inductive Logic Programming Approach to Statistical Relational Learning
Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
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AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Fast hierarchical goal schema recognition
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Multiple-goal recognition from low-level signals
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
A variational learning algorithm for the abstract hidden Markov model
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Activity recognition through goal-based segmentation
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Particle filtering for dynamic agent modelling in simplified poker
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
The hidden permutation model and location-based activity recognition
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Transferring localization models over time
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IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Review: The use of pervasive sensing for behaviour profiling - a survey
Pervasive and Mobile Computing
A general model for online probabilistic plan recognition
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
International Journal of Robotics Research
Accurate and low-cost location estimation using kernels
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Robot introspection through learned hidden Markov models
Artificial Intelligence
Incremental learning of statistical motion patterns with growing hidden Markov models
IEEE Transactions on Intelligent Transportation Systems
Hierarchical control models for multimodal process modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Activity recognition with intended actions
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Delaying commitment in plan recognition using combinatory categorial grammars
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Human activity encoding and recognition using low-level visual features
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
The use of hidden semi-Markov models in clinical diagnosis maze tasks
Intelligent Data Analysis
Unsupervised context detection using wireless signals
Pervasive and Mobile Computing
Active-learning assisted self-reconfigurable activity recognition in a dynamic environment
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
An intrusive intention recognition model based on network security states graph
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Online analysis of hierarchical events in meetings
UI-HCII'07 Proceedings of the 2nd international conference on Usability and internationalization
Multi-view gymnastic activity recognition with fused HMM
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Decomposition in hidden Markov models for activity recognition
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
A relational hierarchical model for decision-theoretic assistance
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Decision detection using hierarchical graphical models
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Recognising Agent Behaviour During Variable Length Activities
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Review: Situation identification techniques in pervasive computing: A review
Pervasive and Mobile Computing
Recognize multi-people interaction activity by PCA-HMMs
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Forecasting complex group behavior via multiple plan recognition
Frontiers of Computer Science in China
Generating artificial corpora for plan recognition
UM'05 Proceedings of the 10th international conference on User Modeling
Human activity monitoring by local and global finite state machines
Expert Systems with Applications: An International Journal
Workflow activity monitoring using dynamics of pair-wise qualitative spatial relations
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Modeling sequences of user actions for statistical goal recognition
User Modeling and User-Adapted Interaction
Human activity recognition with trajectory data in multi-floor indoor environment
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
Journal of Network and Computer Applications
Plan recognition by program execution in continuous temporal domains
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
Discrete relative states to learn and recognize goals-based behaviors of groups
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Hierarchical multi-channel hidden semi Markov graphical models for activity recognition
Computer Vision and Image Understanding
Controlling the hypothesis space in probabilistic plan recognition
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
State-of-the-art of intention recognition and its use in decision making
AI Communications
Intelligent Decision Technologies
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In this paper, we present a method for recognising an agent's behaviour in dynamic, noisy, uncertain domains, and across multiple levels of abstraction. We term this problem on-line plan recognition under uncertainty and view it generally as probabilistic inference on the stochastic process representing the execution of the agent's plan. Our contributions in this paper are twofold. In terms of probabilistic inference, we introduce the Abstract Hidden Markov Model (AHMM), a novel type of stochastic processes, provide its dynamic Bayesian network (DBN) structure and analyse the properties of this network. We then describe an application of the Rao-Blackwellised Particle Filter to the AHMM which allows us to construct an efficient, hybrid inference method for this model. In terms of plan recognition, we propose a novel plan recognition framework based on the AHMM as the plan execution model. The Rao-Blackwellised hybrid inference for AHMM can take advantage of the independence properties inherent in a model of plan execution, leading to an algorithm for online probabilistic plan recognition that scales well with the number of levels in the plan hierarchy. This illustrates that while stochastic models for plan execution can be complex, they exhibit special structures which, if exploited, can lead to efficient plan recognition algorithms. We demonstrate the usefulness of the AHMM framework via a behaviour recognition system in a complex spatial environment using distributed video surveillance data.