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Institute
BTU
RDF/RuleML Interoperability
(2005)
Rule Modeling and Markup
(2005)
Vocabularies, ontologies and rules for enterprise and business process modeling and management
(2010)
100
(2006)
Visual Rules Modeling
(2006)
Agent-Oriented Methodologies
(2005)
What is Negation?
(1999)
In simulation engineering, a system model mainly consists of an information model describing a system's state structure and a process model describing its dynamics. In the fields of Information Systems and Software Engineering, there are widely used standards such as the Class Diagrams of the Unified Modeling Language (UML) for making information models, and the Business Process Modeling Notation (BPMN) for making process models. This tutorial presents a general Object Event Modeling (OEM) approach for Discrete Event Simulation modeling using UML class diagrams and BPMN-based process diagrams at all three levels of model-driven simulation engineering: for making conceptual domain models, for making platform-independent simulation design models, and for making platform-specific, executable simulation models. In this approach, object and event types are modeled as special categories of UML classes, random variables are modeled as a special category of UML operations constrained to comply with a specific probability distribution, and queues are modeled as ordered association ends, while event rules are modeled both as BPMN-based process diagrams and pseudo-code. In Part II, we will discuss the more advanced OEM concepts of activities and GPSS/SIMAN/Arena-style Processing Networks. Finally, in Part III, we will further extend the OEM paradigm towards agent-based modeling and simulation by adding the concepts of agents with perceptions, actions and beliefs.
The term Computer Simulation subsumes different simulation paradigms, languages and implementation technologies as well as many different application areas each with its own scientific communities. So, there is clearly a lot of conceptual, methodological, technological and application diversity in the area of Computer Simulation. From its start in 1967, the Winter Simulation Conference managed to get four scientific communities involved: computer scientists, electrical engineers, industrial engineers and mathematicians (operations researchers). Only later, in 2011 and 2012, an attempt was made to get environmental and social scientists involved who have been adopting the idea of "individual-based" or "agent-based" simulation. Today, two American, a European and an Asian social simulation conference have been established. How much unity exists between the scientific areas and communities represented by the Winter Simulation Conference? How much unity exists between the scientific areas and communities represented by the newer social science simulation conferences? And how much unity exists between Discrete Event Simulation and the newer forms of social science simulation? These and other questions about the unity and diversity of Computer Simulation have been discussed via email from April 17 to May 17, 2018, by five leading experts: Alexis Drogoul, Paul Fishwick, Nigel Gilbert, Dennis Pegden and Levent Yilmaz, moderated by Gerd Wagner.
DPMN is a BPMN-based diagram language for making (computational) process design models for discrete event simulation. It combines the intuitive flowchart modeling style of BPMN with the rigorous semantics provided by the event scheduling arrows of Event Graphs and the event rules of the Object-Event Modeling and Simulation paradigm. While BPMN uses XML Schema as its default type definion
language, DPMN uses UML Class Diagrams as its default (data, object and event) type definion language. As opposed to BPMN Data Objects, DPMN Data Objects instantiate an object type defined by an information model expressed in the form of a UML Class Diagram. A DPMN model has a formal semantics in terms of an Abstract State Machine whose state structure is defined by an object-oriented signature and whose transitions are defined by event rules capturing causal regularities.
Object Event Modeling and Simulation(OEM&S)is a general Discrete Event Simulation paradigm combining object-oriented modeling with the event scheduling paradigm. We show how to extend OEM&S by adding
concepts of agent-based modeling and simulation, resulting in a framework that we call Agent/Object Event Modeling and Simulation (A/OEM&S). The main point for such an extension is to define agents as special objects, which are subject to general (physical) laws of causality captured in the form of event rules, and which have their own behavior allowing them to interact with their inanimate environment and with each other. Because agent behavior is decoupled from physical causality, an A/OE simulator consists of an
environment simulator, which simulates the physical world (the objective states of material objects), and agent simulators, which simulate the internal (subjective) states of agents and their behaviors.
This tutorial presents a model-based approach to developing plain JavaScript web applications with responsive constraint validation, enumeration attributes, uni- and bi-directional associations, and inheritance in class hierarchies. It also shows how to implement the discussed information management concepts and techniques in a generic way in the form of three model-based development libraries: cLASSjs, mODELcLASSjs and mODELvIEWjs.
We define an operational (transition system) semantics for the two most basic forms of Discrete Event Simulation (DES): event-based simulation (without objects) and object-event simulation. We show that under our operational semantics, DES models correspond to a certain form of abstract state machines (ASMs) such that the Future Event List (FEL) is part of the transition system state and the transition func-tion is based on event routines. Unlike other formalisms proposed for DES (such as Petri Nets or DEVS), our ASM semantics takes all basic DES concepts (like event types and the FEL) into consideration and allows for expressive transition system states representing the objects, properties, relations and functions of the evolving possible worlds of a simulation run. As a direct formal semantics of DES, it provides a basis for comparing, and explaining design choices in, different DES approaches.
1
In simulation engineering, a system model mainly consists of an information model and a process model. In the fields of Information Systems and Software Engineering (IS/SE) there are widely used standards such as the Class Diagrams of the Unified Modeling Language (UML) for making information models, and the Business Process Modeling Notation (BPMN) for making process models. This tutorial presents a general approach how to use UML class diagrams and BPMN process diagrams at all three levels of model-driven simulation engineering: for making conceptual simulation models, for making platformindependent simulation design models, and for making platform-specific, executable simulation models. In our approach, object and event types are modeled as stereotyped classes and random variables are modeled as stereotyped operations constrained to comply with a specific probability distribution, while event rules/routines are modeled both as BPMN patterns and in pseudo-code.
The sim4edu.com project website supports web-based simulation with open source technologies for open science and education. It provides both simulation technologies and a library of educational simulation
examples. Its aim is to support both the use and the development of various kinds of simulations, including ad-hoc simulations, Cellular Automata models, NetLogo-style grid space models, discrete event
simulation and agent-based simulation. Sim4edu facilitates building state-of-the-art user interfaces for web-based simulations and simulation games without requiring simulation developers to learn all the recent web technologies involved (e.g., HTML5, CSS3, SVG and WebGL). Using the power of the web, Sim4edu allows researchers and educators to publish and share their models easily.
RuleML Position Statement
(2005)