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Action Programming Languages [electronic resource] / by Michael Thielscher.

By: Thielscher, Michael [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Artificial Intelligence and Machine Learning: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2008Edition: 1st ed. 2008.Description: VIII, 91 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031015472.Subject(s): Artificial intelligence | Machine learning | Neural networks (Computer science)  | Artificial Intelligence | Machine Learning | Mathematical Models of Cognitive Processes and Neural NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Introduction -- Mathematical Preliminaries -- Procedural Action Programs -- Action Programs and Planning -- Declarative Action Programs -- Reactive Action Programs -- Suggested Further Reading.
In: Springer Nature eBookSummary: 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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Introduction -- Mathematical Preliminaries -- Procedural Action Programs -- Action Programs and Planning -- Declarative Action Programs -- Reactive Action Programs -- Suggested Further Reading.

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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