Maintaining Timelines with Hybrid Fuzzy Context Inference

نویسندگان

  • Masoumeh Mansouri
  • Alessandro Saffiotti
چکیده

Timelines allow to represent temporally-rich information about plans as well as the current execution status of plans. Recent work has addressed the related issue of inferring timelines representing contextual information — often useful for informing planning and/or plan execution monitoring processes. The present article addresses the particular issue of inferring context from given models of how observations relate to context, and representing this context on timelines. We strive to abandon assumptions currently made on context recognition, namely that hypotheses are either confirmed or disproved. We propose a technique which allows to accept the inferred context on a timeline with a degree of possibility. The approach is based on fuzzy constraint reasoning, and captures two sources of uncertainty: uncertainty in the model that is used to infer context, and uncertainty in the observations. We also formulate the problem of searching for the most likely timeline as a Constraint Optimization Problem.

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تاریخ انتشار 2012