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|a 9783031015472
|9 978-3-031-01547-2
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|a 10.1007/978-3-031-01547-2
|2 doi
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|a Q334-342
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|a 006.3
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|a Thielscher, Michael.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Action Programming Languages
|h [electronic resource] /
|c by Michael Thielscher.
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|a 1st ed. 2008.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2008.
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|a VIII, 91 p.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Synthesis Lectures on Artificial Intelligence and Machine Learning,
|x 1939-4616
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|a Introduction -- Mathematical Preliminaries -- Procedural Action Programs -- Action Programs and Planning -- Declarative Action Programs -- Reactive Action Programs -- Suggested Further Reading.
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|a Artificial systems that think and behave intelligently are one of the most exciting and challenging goals of Artificial Intelligence. Action Programming is the art and science of devising high-level control strategies for autonomous systems which employ a mental model of their environment and which reason about their actions as a means to achieve their goals. Applications of this programming paradigm include autonomous software agents, mobile robots with high-level reasoning capabilities, and General Game Playing. These lecture notes give an in-depth introduction to the current state-of-the-art in action programming. The main topics are knowledge representation for actions, procedural action programming, planning, agent logic programs, and reactive, behavior-based agents. The only prerequisite for understanding the material in these lecture notes is some general programming experience and basic knowledge of classical first-order logic. Table of Contents: Introduction / Mathematical Preliminaries / Procedural Action Programs / Action Programs and Planning / Declarative Action Programs / Reactive Action Programs / Suggested Further Reading.
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|a Artificial intelligence.
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|a Machine learning.
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|a Neural networks (Computer science) .
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|a Artificial Intelligence.
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|a Machine Learning.
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|a Mathematical Models of Cognitive Processes and Neural Networks.
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783031004193
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|i Printed edition:
|z 9783031026751
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|a Synthesis Lectures on Artificial Intelligence and Machine Learning,
|x 1939-4616
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|u https://doi.uam.elogim.com/10.1007/978-3-031-01547-2
|z Texto Completo
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|a ZDB-2-SXSC
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|a Synthesis Collection of Technology (R0) (SpringerNature-85007)
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