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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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Michael Thielscher is a Professor and head of the Computational Logic Group at Dresden University in Germany since 1997. He received his PhD in Computer Science from Darmstadt University of Technology, Germany. His research is mainly in Knowledge Representation, Cognitive Robotics, Commonsense Reasoning, Game Playing, and Constraint Logic Programming. He has developed the action programming language and system FLUX and has published numerous papers and two books on knowledge representation for actions, on comparisons of different action languages, and on implementations of action programming systems. In 1998, his Habilitation thesis was honored with the award for research excellence by the alumni of Darmstadt University of Technology. He co-authored the program FLUXPLAYER, which in 2006 was crowned the world champion at the Second General Game Playing Competition in Boston.
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