Planning in Intelligent Systems: Aspects, Motivations, and Methods
This text begins with the principle that the ability to anticipate and plan is an essential feature of intelligent systems, whether human or machine. It further assumes that better planning results in greater achievements. With these principles as a foundation, Planning in Intelligent Systems provides readers with the tools needed to better understand the process of planning and to become better planners themselves.
The text is divided into two parts:
* Part One, "Theoretical," discusses the predominant schools of thought in planning: psychology and cognitive science, organizational science, computer science, mathematics, artificial intelligence, and systems theory. In particular, the book examines commonalities and differences among the goals, methods, and techniques of these various approaches to planning. The result is a better understanding of the process of planning through the cross-fertilization of ideas. Each chapter contains a short introduction that sets forth the interrelationships of that chapter to the main ideas featured in the other chapters.
* Part Two, "Practical," features six chapters that center on a case study of The Netherlands Railways. Readers learn to apply theory to a real-world situation and discoverhow expanding their repertoire of planning methods can help solve seemingly intractable problems.
All chapters have been contributed by leading experts in the various schools of planning and carefully edited to ensure a consistent high standard throughout.
This book is designed to not only expand the range of planning tools used, but also to enable readers to use them more effectively. It challenges readers to look at new approaches and learn from new schools of thought. Planning in Intelligent Systems delivers effective planning approaches for researchers, professors, students, and practitioners in artificial intelligence, computer science, cognitive psychology, and mathematics, as well as industry planners and managers.
1. Introduction (Wout van Wezel and Ren&eeacute; Jorna).
PART I: THEORETICAL.
Introduction to Chapter 2.
2. How We Do What We Want: A Neurocognitive Perspective on Human Action Planning (Bernhard Hommel).
Introduction to Chapter 3.
3. Planning in Dynamic Situations: Some Findings in Complex Supervisory Control (Jean-Michel Hoc).
Introduction to Chapter 4.
4. Cognition, Planning, and Domains: An Empirical Study into the Planning Processes of Planners (René Jorna).
Introduction to Chapter 5.
5. Coordination Mechanisms in Multi-Actor Systems (Henk W.M. Gazendam).
Introduction to Chapter 6.
6. The Organizational Interconnectivity of Planning and Scheduling (Kenneth N. McKay and Vincent C.S. Wiers).
Introduction to Chapter 7.
7. Interactive Scheduling Systems (Wout van Wezel).
Introduction to Chapter 8.
8. Mathematical Models for Planning Support (Leo G. Kroon and Rob A. Zuidwijk).
Introduction to Chapter 9.
9. Modeling and Solving Multisite Scheduling Problems (Jürgen Sauer).
Introduction to Chapter 10.
10. Multi-Agent Planning in the Presence of Multiple Goals (Michael H. Bowling, Rune M. Jensen, and Manuela M. Veloso).
Introduction to Chapter 11.
11. Multiresolutional Representation and Behavior Generation: How Does It Affect the Performance of and Planning for Intelligent Systems (Alexander Meystel).
PART II: PRACTICAL.
12. Perspectives on Shunting Planning: Research in Planning Support at the Netherlands Railways (Wout van Wezel and Derk Jan Kiewiet).
13. Task Analysis for Problems of Shunting Planning within the Netherlands Railways (Derk Jan Kiewiet, René Jorna, and Wout van Wezel).
14. Intelligent Shunting: Dealing with Constraints (Satisfaction) (Erwin Abbink).
15. Applying Operations Research Techniques to Planning of Train Shunting (Ramon M. Lentink, Pieter-Jan Fioole, Leo G. Kroon, and Cor van’t Woudt).
16. Train Shunting: A Practical Heuristic Inspired by Dynamic Programming (R. Haijema, C.W. Duin, and N.M. van Dijk).
17. Planner-Oriented Design of Algorithms for Train Shunting Scheduling (J. Riezebos and Wout van Wezel).
18. Conclusions for Intelligent Planning: Diversity and the Quest for Unity (René Jorna, Wout van Wezel, and Alexander Meystel).
RENÉ J. JORNA, PhD, is Professor of Knowledge Management and Cognition, Faculty of Management and Organization, University of Groningen, The Netherlands. His research activities focus on knowledge representation, planning and scheduling, semiotics, knowledge management, and sustainable innovation.
ALEXANDER M. MEYSTEL, PhD, is Professor in the College of Engineering, Drexel University. His research centers on intelligence control, autonomous robots, learning systems, computer architectures for cognitive machines, and manufacturing, as well as the theory of knowledge representation.
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