Data-driven Generation of Policies

This Springer Brief presents a basic algorithm that provides a correct solution to finding an optimal state change attempt, as well as an enhanced algorithm that is built on top of the well-known trie data structure. It explores correctness and algorithmic complexity results for both algorithms and...

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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Parker, Austin (Auteur), Simari, Gerardo I. (Auteur), Sliva, Amy (Auteur), Subrahmanian, V.S (Auteur)
Collectivité auteur: SpringerLink (Online service)
Format: Électronique eBook
Langue:Inglés
Publié: New York, NY : Springer New York : Imprint: Springer, 2014.
Édition:1st ed. 2014.
Collection:SpringerBriefs in Computer Science,
Sujets:
Artificial intelligence.
Data mining.
Database management.
Computer science-Mathematics.
Mathematical statistics.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Database Management.
Probability and Statistics in Computer Science.
Accès en ligne:Texto Completo
Table des matières:
  • Introduction and Related Work
  • Optimal State Change Attempts
  • Different Kinds of Effect Estimators
  • A Comparison with Planning under Uncertainty
  • Experimental Evaluation
  • Conclusions.

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