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Keynote Lectures

Available Soon
Lin Zhang, Beihang University, China

Advances in Hybrid Simulation: Challenges and Research Opportunities from Philosophical, Conceptual and Technological perspectives
Tillal Eldabi, University of Surrey, United Kingdom

Object Event Simulation
Gerd Wagner, Brandenburg University of Technology at Cottbus, Germany

 

Keynote Lecture

Lin Zhang
Beihang University
China
 

Brief Bio
Available Soon


Abstract
Available Soon



 

 

Advances in Hybrid Simulation: Challenges and Research Opportunities from Philosophical, Conceptual and Technological perspectives

Tillal Eldabi
University of Surrey
United Kingdom
 

Brief Bio
Tillal Eldabi is a senior lecturer at Surrey Business School (University of Surrey). His research is mostly focusing on developing frameworks for Hybrid Simulation for modelling complex systems with special emphasis on aspects of modelling healthcare systems. In that regard, he developed tailormade modelling packages to support health economists and clinicians to decide on the best treatment programs. He published widely in highly ranked journals and conferences. He gained funding from national and international research councils such as EPSRC (UK), Qatar National Foundations, British Council, and UNDP – all related to modelling healthcare or Higher Education enhancement. His central believe is that technology and people should work together to enhance productivity and sustainability.


Abstract
Most authors tend to define Hybrid Simulation (HS) as a joint up simulation approach which links two or more simulation techniques (namely, Discrete Event Simulation, System Dynamics, and Agent Based Simulation). Whilst it is commonly argued that HS has been in existence for more than 5 decades, the last decade witnessed a significant surge in HS literature that is more problem-driven rather than mere technical experimentation. The benefits of Hybrid Simulation are well recorded in academic literature. HS is known to offer deeper insights into the real-life system as it allows modellers to assess its inherent problems from different dimensions. This talk provides background to HS, associated challenges, and their respective research opportunities at each of the steps in a typical HS lifecycle (particularly, Philosophical Dovetailing, Conceptual Modelling, Tools Linking, and the Human Factor).



 

 

Object Event Simulation

Gerd Wagner
Brandenburg University of Technology at Cottbus
Germany
 

Brief Bio
Gerd Wagner is Professor of Internet Technology at Brandenburg University of Technology, Cottbus, Germany. After studying Mathematics, Philosophy and Informatics in Heidelberg, San Francisco and Berlin, he (1) investigated the semantics of negation in knowledge representation formalisms, (2) developed concepts and techniques for agent-oriented modeling and simulation, (3) participated in the development of a foundational ontology for conceptual modeling, the Unified Foundational Ontology (UFO), and (4) created a new Discrete Event Simulation paradigm, Object Event Modeling and Simulation (OEM&S), and a new process modeling language, the Discrete Event Process Modeling Notation (DPMN). Much of his recent work on OEM&S and DPMN is available from sim4edu.com and dpmn.info.


Abstract
Object Event Simulation (OES) is a new Discrete Event Simulation (DES) paradigm combining
*object-oriented modeling* with the DES approach of *event scheduling*. An OES design model, providing a computationally complete description of a DES model, consists of an information design model and a process design model. The information design model specifies the types of objects and events that occur in the process design model, while the process design model
defines *causal regularities* involving events as causes and object state changes as well as follow-up events as effects. In this talk, we show how to use UML Class Diagrams and DPMN Process Diagrams, which are based on Event Graphs, for making OES information and process models
and use the JavaScript-based simulation framework OESjs for implementing them. Like Petri Nets and DEVS, OES has a formal semantics. But while Petrie Nets and DEVS are purely computational formalisms without an ontological foundation, OES is based on the ontological categories of
objects, events and causal regularities.



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