Coverart for item
The Resource Data-driven generation of policies, Austin Parker, Gerardo I. Simari, Amy Sliva, V.S. Subrahmanian

Data-driven generation of policies, Austin Parker, Gerardo I. Simari, Amy Sliva, V.S. Subrahmanian

Label
Data-driven generation of policies
Title
Data-driven generation of policies
Statement of responsibility
Austin Parker, Gerardo I. Simari, Amy Sliva, V.S. Subrahmanian
Contributor
Subject
Language
eng
Summary
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
Member of
Dewey number
005.1
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Parker, Austin,
Series statement
SpringerBriefs in Computer Science,
http://library.link/vocab/subjectName
  • Computer algorithms
  • Artificial intelligence
Label
Data-driven generation of policies, Austin Parker, Gerardo I. Simari, Amy Sliva, V.S. Subrahmanian
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
Introduction and Related Work -- Optimal State Change Attempts -- Different Kinds of Effect Estimators -- A Comparison with Planning under Uncertainty -- Experimental Evaluation -- Conclusions
Control code
ocn869219446
Dimensions
unknown
Extent
1 online resource (x, 50 pages)
File format
unknown
Form of item
online
Isbn
9781493902743
Isbn Type
(electronic bk.)
Level of compression
unknown
Other control number
10.1007/978-1-4939-0274-3
Other physical details
illustrations
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)869219446
Label
Data-driven generation of policies, Austin Parker, Gerardo I. Simari, Amy Sliva, V.S. Subrahmanian
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
Introduction and Related Work -- Optimal State Change Attempts -- Different Kinds of Effect Estimators -- A Comparison with Planning under Uncertainty -- Experimental Evaluation -- Conclusions
Control code
ocn869219446
Dimensions
unknown
Extent
1 online resource (x, 50 pages)
File format
unknown
Form of item
online
Isbn
9781493902743
Isbn Type
(electronic bk.)
Level of compression
unknown
Other control number
10.1007/978-1-4939-0274-3
Other physical details
illustrations
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)869219446

Library Locations

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