---
abstract: 'Real-world agents must react to changing conditions as they execute planned tasks. Conditions are typically monitored through time series representing state variables. While some predicates on these times series only consider one measure at a time, other predicates, sometimes called episodic predicates, consider sets of measures. We consider a special class of episodic predicates based on segmentation of the the measures into quasi-monotonic intervals where each interval is either quasi-increasing, quasi-decreasing, or quasi-flat. While being scale-based, this approach is also computational efficient and results can be computed exactly without need for approximation algorithms. Our approach is compared to linear spline and regression analysis.'
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confdates: 2005
conference: 'AAAI-05: Twentieth National Conference on Artificial Intelligence'
confloc: Pittsburg USA
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creators_name:
  - family: Fitzgerald
    given: Will
    honourific: ''
    lineage: ''
  - family: Lemire
    given: Daniel
    honourific: ''
    lineage: ''
  - family: Brooks
    given: Martin
    honourific: ''
    lineage: ''
date: 2005
date_type: published
datestamp: 2005-08-06
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dir: disk0/00/00/44/96
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eprintid: 4496
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full_text_status: public
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lastmod: 2011-03-11 08:56:09
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rev_number: 12
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status_changed: 2007-09-12 17:00:20
subjects:
  - comp-sci-art-intel
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title: Quasi-monotonic segmentation of state variable behavior for reactive control
type: confpaper
userid: 4175
volume: ~
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