Interleaved Inductive-Abductive Reasoning for Learning Event-Based Activity Models
نویسنده
چکیده
We propose an interleaved inductive-abductive model for reasoning about complex spatio-temporal narratives. Typed Inductive Logic Programming (Typed-ILP) is used as a basis for learning the domain theory by generalising from observation data, whereas abductive reasoning is used for noisy data correction by scenario and narrative completion thereby improving the inductive learning to get semantically meaningful event models. We apply the model to an airport domain consisting of video data for 10 turn-arounds.
منابع مشابه
Interleaved Inductive-Abductive Reasoning for Learning Complex Event Models
We propose an interleaved inductive-abductive model for reasoning about complex spatio-temporal narratives. Typed Inductive Logic Programming (Typed-ILP) is used as a basis for learning the domain theory by generalising from observation data, whereas abductive reasoning is used for noisy data correction by scenario and narrative completion thereby improving the inductive learning to get semanti...
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تاریخ انتشار 2011