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Krüger,  Frank

Activity, context, and plan recognition with computational causal behavior models

Rostock : Universität , 2018

https://doi.org/10.18453/rosdok_id00002015

http://purl.uni-rostock.de/rosdok/id00002015

Objective of this thesis is to answer the question "how to achieve efficient sensor-based reconstruction of causal structures of human behaviour in order to provide assistance?". To answer this question, the concept of Computational Causal Behaviour Models (CCBMs) is introduced. CCBM allows the specification of human behaviour by means of preconditions and effects and employs Bayesian filtering techniques to reconstruct action sequences from noisy and ambiguous sensor data. Furthermore, a novel approximative inference algorithm – the Marginal Filter – is introduced.

Dissertation Open Access


Einrichtung :
Fakultät für Informatik und Elektrotechnik
Gutachter :
Kirste,  Thomas  (Dr.-Ing.)
Uhrmacher,  Adelinde  (Dr. rer. nat.)
Ortmeier,  Frank  (Dr.-Ing.)
Jahr der Abgabe:
2016
Jahr der Verteidigung:
2016
Sprache(n) :
Englisch
Schlagworte:
artificial intelligence, probabilistic inference, inverse planning, ubiquituous computing
DDC Klassifikation :
004 Informatik
URN :
urn:nbn:de:gbv:28-diss2018-0009-0
Persistente URL:
http://purl.uni-rostock.de/rosdok/id00002015
erstellt am:
2018-01-26
zuletzt geändert am:
2018-06-30
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