Object-Oriented Simulation with Hierarchical, Modular Models

Object-Oriented Simulation with Hierarchical, Modular Models

Intelligent Agents and Endomorphic Systems

1st Edition - March 28, 1990

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  • Author: Bernard P. Zeigler
  • eBook ISBN: 9781483264912

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Object-Oriented Simulation with Hierarchical, Modular Models: Intelligent Agents and Endomorphic Systems describes an approach to object-oriented discrete event simulation and the concepts of hierarchical, modular model construction, The implementation of the concepts of multifaceted modeling methodology in the DEVS-Scheme modeling and simulation environment is discussed. The use of the DEVS-Scheme environment in modeling artificial intelligent agents is also considered, along with the concept of endomorphism to characterize the application of self-embedded models, including models of self. Comprised of 15 chapters, this book begins with an overview of the dimensions of knowledge representation in simulation environments, followed by a discussion on object-oriented programming as well as the concepts of modular, hierarchical models and the system entity structure. Subsequent chapters focus on digraph-models and experimental frames; DEVS formalism and DEVS-Scheme simulation environment; a model base for simple multi-computer architectures; and rule-based specification of atomic models. Model bases in endomorphic systems and intelligent agents are also examined. This monograph will be of interest to simulation theorists as well as practitioners and researchers in the fields of artificial intelligence, systems engineering, computer science and engineering, and operations research.

Table of Contents

  • Preface

    1 Dimensions of Knowledge Representation in Simulation Environments

    1.1 Introduction

    1.2 Knowledge Representation Schemes and Formalisms

    1.3 Simulation Model Specification Formalisms

    1.4 AI Knowledge Representation Schemes

    1.5 Representation and Knowledge

    1.6 System-Theoretic Representation

    1.7 Modular, Hierarchical Models and Object-Oriented Paradigms Contrasted

    1.8 Framework for Knowledge Representation in Simulation

    1.9 What Kinds of Modelling and Simulation Knowledge Are There?

    1.10 Endomorphic Models, Simulations, and Agents

    2 Basics

    2.1 Object-Oriented Programming Concepts

    2.2 The System Entity Structure/Model Base

    2.3 Independent Testability

    2.4 Artificial Worlds Example

    2.5 SES Pruning and Model Synthesis

    3 DEVS Formalism and Devs-Scheme

    3.1 Discrete Event Dynamic Systems

    3.2 Brief Review of the DEVS Formalism

    3.3 Basic Models

    3.4 Coupled Models

    3.5 DEVS-Scheme Simulation Environment

    4 Atomic-Models: Simple Processor Example

    4.1 Performance of Simple Architectures

    4.2 A Simple Processor Model

    4.3 Normal Form Atomic Model Specification

    4.4 DEVS-Scheme Atomic Model Implementation of Simple Processor

    4.5 Simulation of Atomic Models

    4.6 Stand-Alone Testing of an Atomic Model

    4.7 Simple Processor with Buffering and Random Processing Times

    5 Digraph-Models and Experimental Frames

    5.1 Experimental Frame for Simple Computer Architectures

    5.2 Development of Digraph-Models

    5.3 Co-Ordinator of Coupled-Models

    5.4 Applicability of Frames to Models: Model Instrumentation

    6 A Model Base for Simple Multicomputer Architectures

    6.1 Co-Ordinators and Architectures

    6.2 Testing the Architectures

    7 System Entity Structures

    7.1 System Entity Structure Definitions and Axioms

    7.2 Using the System Entity Structure in DEVS-Scheme

    7.3 System Entity Structure Organization of Model Bases

    7.4 Operations on Hierarchical Model Structures: Flatting and Deepening

    8 Advanced Devs Concepts and Kernel-Models

    8.1 More Advanced Processor Models

    8.2 Kernel-Models: Homogeneous Structures

    8.3 Example: Parallel Processor Broadcast Architecture

    8.4 Methods Make-new and Make-class

    8.5 System Entity Structure Representation of Kernel Models

    8.6 Multilayered Models and Distributed Experimental Frames

    9 Rule-Based Specification of Atomic-Models

    9.1 Activities as Rules

    9.2 Class Forward-Models

    9.3 Inheritance and Specialization

    9.4 Specialization and Multiple Entities

    9.5 DEVS-Scheme Methodology Reviewed

    10 A Robot-Managed Laboratory of the Future

    10.1 Multilevel Hierarchical Robot Model

    10.2 Space Management for Mobile Components

    10.3 Robot Cognition System

    10.4 Robot-Managed Laboratory Model

    11 Endomorphy: Models within Intelligent Agents

    11.1 Approach to Endomorphy: Multifacetted Modelling Methodology

    11.2 Process Laboratory Model

    11.3 Robot Models: Designing Model-Plan Units

    11.4 DEVS Representation of Dynamic Systems

    11.5 Obtaining the Characteristic Functions of the DEVS Model

    11.6 Robot Fluid Handling MPUs

    11.7 Table-Models: Deriving Internal Models from External Models

    11.8 Windows in Table-Models: Parameter Sensitivity Analysis

    12 Endomorphy: Model Usage within Intelligent Agents

    12.1 Event-Based Control

    12.2 Using DEVS Models of Processes to Construct Event-Based Control Models

    12.3 Introspection and Super-Simulation

    12.4 Table-Models: Command Sequence Planning

    12.5 Breakdown Diagnosis

    12.6 Testing MPU Designs

    12.7 Summary: Methodology for Event-Based Control

    13 Model Base Management and Endomorphic Systems

    13.1 Reuse of Pruned Entity Structures

    13.2 Hierarchical Reuse of PES Versions

    13.3 Partitioned System Entity Structures

    13.4 Context Sensitive Pruning

    13.5 Model Coherence and Context Sensitive Constraint Rules

    13.6 Model Bases in Endomorphic Systems and Intelligent Agents

    13.7 Minsky's Views on Models and Knowledge

    14 DEVS-Scheme in the Larger Scheme of Things

    14.1 Layers of DEVS-Scheme

    14.2 Other Properties, Other Views

    15 Epilogue: The Challenge of High Autonomy Systems

    A Advanced Concepts and Facilities

    A.1 Continuous Model Extensions to DEVS-Scheme

    A.2 Simulation of Multi-Formalism Non-Homogeneous Networks

    A.3 Distributed Simulation of DEVS Models

    A.4 Automated Hierarchical Model Simplification

    A.5 Variable Structure Models

    A.6 Using Object-Oriented Concepts to Support Extensibility of Layer 1 with Respect to Layer 2

    A.7 Converting Non-Modular to Modular Form

    B DEVS and GSMP: Some Relations

    B.1 Some Simple Behaviors of DEVS

    B.2 Proof that the DEVS Behaviors Require Uncountable State Sets

    B.3 Expressing GSMP within DEVS



Product details

  • No. of pages: 414
  • Language: English
  • Copyright: © Academic Press 1990
  • Published: March 28, 1990
  • Imprint: Academic Press
  • eBook ISBN: 9781483264912

About the Author

Bernard P. Zeigler

Bernard P. Zeigler, is a Professor of Electrical & Computer Engineering at the University of Arizona and co-director of the Arizona Center for Integrative Modeling and Simulation. He is the author of numerous books and publications, a Fellow of the IEEE, and of the Society for Modeling and Simulation International.

Zeigler is currently heading a project for the Joint Interoperability Test Command (JITC) where he is leading the design of the future architecture for large distributed simulation events for the Joint Distributed Engineering Plant (JDEP). He is also developing DEVS-methodology approaches for testing mission thread end-to-end interoperability and combat effectiveness of Defense Department acquisitions and transitions to the Global Information Grid with its Service Oriented Architecture (GIG/SOA).

Affiliations and Expertise

University of Arizona, Tucson, USA

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