Unified theories of cognition
A computational scheme for reasoning in dynamic probabilistic networks
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
A Bayesian model of plan recognition
Artificial Intelligence
Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
Generalized Queries on Probabilistic Context-Free Grammars
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulation-based inference for plan monitoring
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Statistical Language Learning
Probabilistic grammars for plan recognition
Probabilistic grammars for plan recognition
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Towards history-based grammars: using richer models for probabilistic parsing
HLT '91 Proceedings of the workshop on Speech and Natural Language
A message passing algorithm for plan recognition
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Effective Bayesian inference for stochastic programs
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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
Accounting for context in plan recognition, with application to traffic monitoring
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Plan recognition in exploratory domains
Artificial Intelligence
Forecasting complex group behavior via multiple plan recognition
Frontiers of Computer Science in China
Modeling sequences of user actions for statistical goal recognition
User Modeling and User-Adapted Interaction
Controlling the hypothesis space in probabilistic plan recognition
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Robotics and artificial intelligence: A perspective on deliberation functions
AI Communications - ECAI 2012 Turing and Anniversary Track
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Techniques for plan recognition under uncertainty require a stochastic model of the plangeneration process. We introduce probabilistic state-dependent grammars (PSDGs) to represent an agent's plan-generation process. The PSDG language model extends probabilistic contextfree grammars (PCFGs) by allowing production probabilities to depend on an explicit model of the planning agent's internal and external state. Given a PSDG description of the plan-generation process, we can then use inference algorithms that exploit the particular independence properties of the PSDG language to efficiently answer plan-recognition queries. The combination of the PSDG language model and inference algorithms extends the range of plan-recognition domains for which practical probabilistic inference is possible, as illustrated by applications in traffic monitoring and air combat.