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What and Who
Title:Results of planning for sentence generation
Speaker:Khansa Rekik
coming from:International Max Planck Research School for Computer Science - IMPRS
Speakers Bio:IMPRS-CS Master Student
Event Type:IMPRS Research Seminar
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Monday, 30 October 2017
Duration:30 Minutes
Building:E1 4
Natural language generation is translated to a planning problem in order to benefit from off-the-shelf planners. The efficiency
of FF and SGPLAN is tested with the sentence generation problem as well as the instruction giving domain and
compared to other conventional tools. Experiments have been made using different configurations. An important amount
of time of the total running time has been allocated to the grounding/parsing step which is not necessarily useful in this
application. To solve this problem for the FF planner, some fixes has been performed. As a first step to make the preprocessing
phase less exhausting, hard processors have been eliminated. Second, action pruning and helpful actions techniques
have been adopted.
Name(s):IMPRS-CS Office Team
Phone:0681 93251802
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:NoTo Location:
Tags, Category, Keywords and additional notes
Attachments, File(s):
Stephanie Jörg/MPI-INF, 10/27/2017 12:56 PM
Last modified:
Uwe Brahm/MPII/DE, 10/30/2017 07:00 AM
  • Stephanie Jörg, 10/27/2017 12:59 PM -- Created document.