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team:daniel_nyga [2017/06/16 09:27] – [Dissertation] nyga | team:daniel_nyga [2017/06/16 11:46] – [Fields of Interest] nyga | ||
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vagueness and ambiguity in natural language and infer missing | vagueness and ambiguity in natural language and infer missing | ||
information pieces that are required to render an instruction | information pieces that are required to render an instruction | ||
- | executable by a robot. To this end, \prac formulates the problem of | + | executable by a robot. To this end, PRAC formulates the problem of |
instruction interpretation as a reasoning problem in first-order | instruction interpretation as a reasoning problem in first-order | ||
probabilistic knowledge bases. In particular, the system uses Markov | probabilistic knowledge bases. In particular, the system uses Markov | ||
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He is the lead developer in the projects [[http:// | He is the lead developer in the projects [[http:// | ||
- | His GitHub profile can be found [[http:// | + | His GitHub profile can be found [[http:// |
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* Data Mining/ | * Data Mining/ | ||
* Automated Learning/ | * Automated Learning/ | ||
- | * Natural-Language Understanding | + | * Natural-language understanding |
====Teaching==== | ====Teaching==== |
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
Contact via
Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de
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