The mathematics of inheritance systems
The mathematics of inheritance systems
Plan recognition for intelligent interfaces
Proceedings of the sixth conference on Artificial intelligence applications
Representing and reasoning with probabilistic knowledge
Representing and reasoning with probabilistic knowledge
Reasoning about Movement in Two-Dimensions
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
Activity Recognition for Dynamic Multi-Agent Teams
ACM Transactions on Intelligent Systems and Technology (TIST)
Probabilistic state-dependent grammars for plan recognition
UAI'00 Proceedings of the Sixteenth 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
The automated mapping of plans for plan recognition
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
A probabilistic network of predicates
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
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We present a general framework for plan recognition whose formulation is motivated by a general purpose algorithm for effective abduction. The knowledge representation is a restricted form of first order logic, which is made computationally explicit as a graph structure in which plans are manifest as a special kind of graph walk. Intuitively, plans are fabricated by searching an action description graph for relevant connections amongst instances of observed actions. The class of plans for which our method is applicable is wider than those previously proposed, as both recursive and optional plan components can be represented. Despite the increased generality, the proposed message-passing algorithm has an asymptotic upper bound that is an improvement on previous related work.