Modelling and Simulation Methodology
Knowledge Systems' Paradigms
Published in August 1989
Book
Hardback
500 pages
978-0-444-88044-4 (ISBN)
Description
These papers are grouped into five coherent sections. The first section sets the basis for the rest of the book by addressing fundamental issues. The second section is devoted to specialized computer environments that make Modelling and Simulation easier to perform correctly, while the third section reflects the impact of rule-based methodologies (originated in the AI field) on the world of Modelling and Simulation. Section Four stands in a class of its own as it is based on a novel methodology that in itself is modelled on a biological process, providing promising inroads into the world of adaptive and self-learning methods. The last section describes various applications of the principles to generalised problems of modelling and design.
These papers are grouped into five coherent sections. The first section sets the basis for the rest of the book by addressing fundamental issues. The second section is devoted to specialized computer environments that make Modelling and Simulation easier to perform correctly, while the third section reflects the impact of rule-based methodologies (originated in the AI field) on the world of Modelling and Simulation. Section Four stands in a class of its own as it is based on a novel methodology that in itself is modelled on a biological process, providing promising inroads into the world of adaptive and self-learning methods. The last section describes various applications of the principles to generalised problems of modelling and design.
These papers are grouped into five coherent sections. The first section sets the basis for the rest of the book by addressing fundamental issues. The second section is devoted to specialized computer environments that make Modelling and Simulation easier to perform correctly, while the third section reflects the impact of rule-based methodologies (originated in the AI field) on the world of Modelling and Simulation. Section Four stands in a class of its own as it is based on a novel methodology that in itself is modelled on a biological process, providing promising inroads into the world of adaptive and self-learning methods. The last section describes various applications of the principles to generalised problems of modelling and design.
More details
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Illustrations
Illustrations
Dimensions
Height: 230 mm
ISBN-13
978-0-444-88044-4 (9780444880444)
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Schweitzer Classification
Content
Paradigms and Methodological Bases. The Role of AI/Entity Structure Concept Manipulation Methods in System Modelling and Design (M.S. Elzas). Bases for Advanced Simulation: Paradigms for the Future (T.I. Oren). Concepts for Distributed Knowledge Maintenance in Variable Structure Models (B.P. Zeigler). Inductive Systems Modelling: An Overview (G.J. Klir). An Adaptive, Selfmodifying, Non Goal Directed Modelling Methodology (P. Hogeweg, B. Hesper). On the Foundations of Knowledge Engineering (R.A. Orchard, E.J. Reese, M.R. Tausner). Aspects of Qualitative Reasoning and Simulation for Knowledge Intensive Problem Solving (S.L. Hardt). Environments. MASCOT: A Prolog-Based Simulation Modelling and Training Environment (G.T. Mackulak, J.K. Cochran). Towards Automated Model Development and Validation for Crop Production (J.M. McKinion). SIMSMART: Dynamic Simulation for Automated Control and Optimization of Complex Industrial Processes (D. Waye, A. Terroux, M. Walters). The SIMKIT TM : Knowledge-Based Simulation Tools (D. Silverman, M. Stelzner). An Interactive System for Continuous Simulation Problems (R.L. Peskin, M.F. Russo, A.D. Kowalski). Rule Based Modelling and Simulation. A Knowledge-Based Modelling and Simulation Tool (H. Gallaire). Modelling and Simulation in Hardware Troubleshooting (F. Malabocchia). Formalization of Tradeoff Rules and Other Techniques for Comprehending Rule-Based Models (P.K. Davis, S.C. Bankes, R. Weissler). ROBS: Rules and Objects Based Simulation (A. Radiya, R.G. Sargent). Rule Based Discrete System Simulation and Verification of Petri Nets (D. Duan). System Knowledge, Contexts and Natural Language (K. Kornwachs). Genetic Based Methodology. Genetics-Based Machine Learning (D.E. Goldberg). Modelling Emergent Properties of Biological Systems (M.M. Rizki). Optimizing Network Link Sizes with Genetic Algorithms (L. Davis, S. Coombs). Modelling High-Level Symbolic Structures in Parallel Systems that Support Learning (S. Forrest). Hierarchical Credit Allocation in a Classifier System (S.W. Wilson). Learning Plateaus in an Adaptive Rule-Based System (C.P. Stackhouse, B.P. Zeigler). Applications. A Learning Behaviour Model of Hierarchical Automata in a Nonstationary Multiteacher Environment (N. Baba). Abstraction Level Traversal in Hierarchical Modelling (P.A. Fishwick). Implementing Methodology-Based Tools in DEVS-Scheme (B.P. Zeigler et al.). Experimental Frame Generation in a Knowledge-Based System Design and Simulation Environment (J.W. Rozenblit, J.F. Hu). Subject Index.