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team:daniel_nyga [2013/06/25 14:16] – [About] nygateam:daniel_nyga [2013/07/03 15:22] – [About] nyga
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 My work aims at building up action-specific knowledge bases from various knowledge sources, such as natural language, interactive computer games, observations of humans performing everyday activity or experience data of a robot. My work aims at building up action-specific knowledge bases from various knowledge sources, such as natural language, interactive computer games, observations of humans performing everyday activity or experience data of a robot.
  
-{{people:nyga:actioncore.png?w=700&h=65&t=1357297411}}+{{research:actioncore.png?w=620&h=65&t=1357297411}}
  
 Knowledge about actions and objects is represented as //Probabilistic Robot Action Cores (PRAC)//, which can be thought of generic event patterns that enable a robot to infer important information that is missing in an original natural-language instruction. PRAC models are represented in //Markov Logic Networks//, a powerful knowlegde represenation formalism combing first-order logic and probability theory. Knowledge about actions and objects is represented as //Probabilistic Robot Action Cores (PRAC)//, which can be thought of generic event patterns that enable a robot to infer important information that is missing in an original natural-language instruction. PRAC models are represented in //Markov Logic Networks//, a powerful knowlegde represenation formalism combing first-order logic and probability theory.
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Prof. Dr. hc. Michael Beetz PhD
Head of Institute

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Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de

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