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Abductive Plan Recognition by Extending Bayesian Logic Programs
Published on Nov 30, 20112837 Views
Plan recognition is the task of predicting an agent’s top-level plans based on its observed actions. It is an abductive reasoning task that involves inferring cause from effect. Most existing approach
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Chapter list
Abductive Plan Recognition By Extending Bayesian Logic Programs00:00
Plan Recognition00:17
Plan Recognition in Intelligent User Interfaces00:52
Related Work02:30
Our Approach04:14
Outline - 104:59
Logical Abduction05:17
Bayesian Logic Programs (BLPs)05:58
Inference in BLPs07:05
BLPs for Plan Recognition07:59
Extending BLPs for Plan Recognition08:40
Logical Abduction in BALPs08:54
Example – Intelligent User Interfaces09:33
Abductive Inference - 110:15
Abductive Inference - 210:43
Abductive Inference - 310:55
Abductive Inference - 411:18
Structure of Bayesian network11:30
Probabilistic Inference - 111:34
Probabilistic Inference - 212:22
Probabilistic Inference - 312:46
Probabilistic Inference - 413:48
Probabilistic Inference - 513:50
Probabilistic Inference - 613:53
Probabilistic Inference - 713:55
Probabilistic Inference - 814:00
Parameter Learning14:05
Experimental Evaluation14:52
Monroe and Linux - 115:06
Monroe and Linux - 216:02
Results on Monroe - 116:52
Results on Linux - 117:03
Experiments with partial observability17:09
Results on Monroe - 218:59
Results on Linux - 219:29
Story Understanding - 119:38
Story Understanding - 220:03
Results on Story Understanding20:35
Conclusion21:03
Future Work21:26
Questions21:38