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    <link>http://hdl.handle.net/2117/6033</link>
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    <pubDate>Thu, 23 May 2013 03:00:41 GMT</pubDate>
    <dc:date>2013-05-23T03:00:41Z</dc:date>
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      <itunes:email>webmaster.bupc@upc.edu</itunes:email>
      <itunes:name>Universitat Politècnica de Catalunya. Servei de Biblioteques i Documentació</itunes:name>
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      <title>A general strategy for interactive decision-making in robotic platforms</title>
      <link>http://hdl.handle.net/2117/13951</link>
      <description>Title: A general strategy for interactive decision-making in robotic platforms
Authors: Agostini, Alejandro Gabriel; Torras, Carme; Wörgötter, Florentin
Abstract: This work presents an intergated strategy for planning and learning suitable to execute tasks with robotic platforms without any previous task specification. The approach rapidly learns planning operators from few action experiences using a competitive strategy where many alternatives of cause-effect explanations are evaluated in parallel, and the most successful ones are used to generate the operators. The system operates without task interruption by integrating in the planning-learning loop a human teacher that supports the planner in making decisions. All the mechanisms are integrated and synchronized in the robot using a general decision-making framework.</description>
      <pubDate>Thu, 17 Nov 2011 10:49:57 GMT</pubDate>
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      <dc:date>2011-11-17T10:49:57Z</dc:date>
      <itunes:author>Agostini, Alejandro Gabriel; Torras, Carme; Wörgötter, Florentin</itunes:author>
      <itunes:explicit>no</itunes:explicit>
      <itunes:keywords>Learning (artificial intelligence) &#xD;
Planning (artificial intelligence)</itunes:keywords>
      <itunes:summary>This work presents an intergated strategy for planning and learning suitable to execute tasks with robotic platforms without any previous task specification. The approach rapidly learns planning operators from few action experiences using a competitive strategy where many alternatives of cause-effect explanations are evaluated in parallel, and the most successful ones are used to generate the operators. The system operates without task interruption by integrating in the planning-learning loop a human teacher that supports the planner in making decisions. All the mechanisms are integrated and synchronized in the robot using a general decision-making framework.</itunes:summary>
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      <title>Hybrid Landscape: report 06.07: afterword</title>
      <link>http://hdl.handle.net/2117/10507</link>
      <description>Title: Hybrid Landscape: report 06.07: afterword
Authors: Sabaté Bel, Joaquín</description>
      <pubDate>Thu, 09 Dec 2010 13:54:31 GMT</pubDate>
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      <dc:date>2010-12-09T13:54:31Z</dc:date>
      <itunes:author>Sabaté Bel, Joaquín</itunes:author>
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      <title>Anàlisis per a la valoració de la normativa del 22@</title>
      <link>http://hdl.handle.net/2117/9170</link>
      <description>Title: Anàlisis per a la valoració de la normativa del 22@
Authors: Domingo Domingo, Carmen; Ferrer Forés, Jaime Jose; Rahola Aguadé, Víctor; Crosas Armengol, Carles; Galindo González, Julián; Franquesa Sànchez, Jordi; Sagarra Trias, Ferran; Goula, Maria</description>
      <pubDate>Wed, 29 Sep 2010 15:30:24 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/2117/9170</guid>
      <dc:date>2010-09-29T15:30:24Z</dc:date>
      <itunes:author>Domingo Domingo, Carmen; Ferrer Forés, Jaime Jose; Rahola Aguadé, Víctor; Crosas Armengol, Carles; Galindo González, Julián; Franquesa Sànchez, Jordi; Sagarra Trias, Ferran; Goula, Maria</itunes:author>
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