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Libro

Data-driven Generation of Policies

Parker, Austin; Simari, GerardoIcon ; Sliva, Amy; Subrahmanian, Venkatramanan
Fecha de publicación: 2014
Editorial: Springer
ISSN: 2191-5768
e-ISSN: 2191-5776
ISBN: 978-1-4939-0273-6
Idioma: Inglés
Clasificación temática:
Ciencias de la Computación

Resumen

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 experiments comparing their performance on both real-world and synthetic data. Topics addressed include optimal state change attempts, state change effectiveness, different kind of effect estimators, planning under uncertainty and experimental evaluation. These topics will help researchers analyze tabular data, even if the data contains states (of the world) and events (taken by an agent) whose effects are not well understood. Event DBs are omnipresent in the social sciences and may include diverse scenarios from political events and the state of a country to education-related actions and their effects on a school system. With a wide range of applications in computer science and the social sciences, the information in this Springer Brief is valuable for professionals and researchers dealing with tabular data, artificial intelligence and data mining. The applications are also useful for advanced-level students of computer science.
Palabras clave: AUTOMATIC POLICY GENERATION , DATA-DRIVEN INFORMATION SYSTEMS , EFFECT ESTIMATORS , EVENT DATABASES , TRIE DATA STRUCTURE
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Tamaño: 1.492Mb
Formato: PDF
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Licencia
info:eu-repo/semantics/closedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/135399
URL: http://www.springer.com/computer/ai/book/978-1-4939-0273-6
DOI: https://doi.org/10.1007/978-1-4939-0274-3
Colecciones
Libros(CCT - BAHIA BLANCA)
Libros de CTRO.CIENTIFICO TECNOL.CONICET - BAHIA BLANCA
Citación
Parker, Austin; Simari, Gerardo; Sliva, Amy; Subrahmanian, Venkatramanan; Data-driven Generation of Policies; Springer; 2014; 60
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