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Data-driven Generation of Policies by Amy Sliva, Gerardo I. Simari, Austin Parker, V.S. Subrahmanian (Paperback, 2014)

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About this product

Product Information

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.

Product Identifiers

Publisher
Springer-Verlag New York Inc.
ISBN-13
9781493902736
eBay Product ID (ePID)
189471226

Product Key Features

Author
Amy Sliva, Gerardo I. Simari, Austin Parker, V.S. Subrahmanian
Publication Name
Data-Driven Generation of Policies
Format
Paperback
Language
English
Subject
Computer Science
Publication Year
2014
Type
Textbook
Number of Pages
50 Pages

Dimensions

Item Height
235mm
Item Width
155mm
Item Weight
1066g

Additional Product Features

Title_Author
Austin Parker, Amy Sliva, Gerardo I. Simari, V.S. Subrahmanian
Series Title
Springerbriefs in Computer Science
Country/Region of Manufacture
United States

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