Relational Reinforcement Learning for Planning with Exogenous Effects

Probabilistic planners have improved recently to the point that they can solve difficult tasks with complex and expressive models. In contrast, learners cannot tackle yet the expressive models that planners do, which forces complex models to be mostly handcrafted. We propose a new learning approach...

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Veröffentlicht in:	Journal of machine learning research 2017-08, Vol.18, p.1-44
Hauptverfasser:	Martinez, David, Alenya, Guillem, Ribeiro, Tony, Inoue, Katsumi, Torras, Carme
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Computer Science Logic in Computer Science Machine Learning Robotics
Online-Zugang:	Volltext
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