Tuncer I. Ören

Concepts for advanced simulation methodologies

Conventional simulation techniques have three short comings when applied to large-scale modelling : They provide an inadequate man-machine interface, they provide a poor conceptual framework, and they lack needed tools for managing data and model. These shortcomings may be ameliorated by developing new simulation languages that differentiate the function aZ elements of simulation programs and by recognizing the goals of these functional elements. This paper provides concepts for the design and implementation of such advanced simulation methodologies.

Concepts and criteria to assess acceptability of simulation studies: a frame of reference

The existing trend of application of computerized simulation studies to large and complex systems necessitates the development of an assessment methology for simulation studies. The basic concepts and criteria necessary for such an assessment methodology are presented in a systematic way. The proposed framework permits discussion of the concepts and criteria related to the acceptability of the following components of a simulation study: Simulation results, real world and simulated data, parametric model and the values of the model parameters, specification of the experimentation, representation and execution of the computer program, and modeling, experimentation, simulation, and programming methodologies or techniques used. The acceptability of the components of a simulation study are discussed with respect to the goal of the simulation study, the structure and data of the real system, the parametric model, the model parameter set, the specification of the experimentation, and the existing or conceivable norms of modeling methodology, experimentation technique, simulation methodology, and software engineering.

Simulation and Model-Based Methodologies: An Integrative View

Thank you very much for reading simulation and model based methodologies an integrative view. As you may know, people have look numerous times for their favorite books like this simulation and model based methodologies an integrative view, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their desktop computer.Section 1: Conceptual Bases for System Modelling and Design.- 1: Model-Based Activities: A Paradigm Shift.- 2: System Paradigms as Reality Mappings.- 3: General Systems Framework for Inductive Modelling.- 4: System Theoretic Foundations of Modelling and Simulation.- 5: The Tricotyledon Theory of System Design.- 6: Concepts for Model-Based Policy Construction.- Section 2: Model-Based Simulation Architecture.- 7: Structures for Model-Based Simulation Systems.- 8: Symbolic Manipulation of System Models.- 9: Concepts for an Advanced Parallel Simulation Architecture.- Section 3: Impact of Formalisms on Model Specification.- 10: GEST-A Modelling and Simulation Language Based on System Theoretic Concepts.- 11: Continuous and Discontinuous-Change Models: Concepts for Simulation Languages.- 12: Discrete Event Formalism and Simulation Model Development.- Section 4: Model Identification, Reconstruction, and Optimization.- 13: Structure Characterization for I11-Defined Systems.- 14: Reconstructability Analysis: An Overview.- 15: SAPS-A Software System for Inductive Modelling.- 16: Optimization in Simulation Studies.- Section 5: Quality Assurance in Model-Based Activities.- 17: Quality Assurance in Modelling and Simulation: A Taxonomy.- 18: How to Enhance the Robustness of Simulation Software.- 19: Simulation Model Validation.- 20: Critical Issues in Evaluating Socio-Economic Models.- Section 6: Contributed Workshop Presentations.- Group 1: Model-Based Simulation Architecture.- Group 2: Impact of Formalisms on Model Specification.- Group 3: Model Identification, Reconstruction, and Optimization.- Group 4: Quality Assurance in Model-Based Activities.

Agent-directed simulation systems engineering

This article emphasizes the application of system engineering principles to the development of Modeling and Simulation (M&S) applications. Clear distinction between M&S for system engineering and system engineering (SE) for M&S is presented to clarify the need for simulation system engineering. Furthermore, the characteristics of emergent open, complex, and adaptive M&S applications are overviewed to make the case for agent-directed simulation system engineering. An agent-directed simulation view of developing such applications is presented within the framework of a cognitive system engineering perspective.

Dynamic templates and semantic rules for simulation advisors and certifiers

Discontinuity is conceived from a new point of view. The new causal paradigm leads to the concepts “model update” and “multimodel.” Based on this new paradigm, several problem-oriented (as opposed to implementation oriented) modelling formalisms are specified as dynamic templates. The templates can be embedded in advanced modelling and simulation environments and can be automatically tailored according to the requirements of the problem.

Requirements and design principles for multisimulation with multiresolution, multistage multimodels

The significance of simulation modeling at multiple levels, scales, and perspectives is well recognized. However, existing proposals for developing such models are often application specific. The position advocated in this paper is that generic design principles for specifying and realizing multiresolution, multistage models are still lacking. Requirements for simulation environments that facilitate multiresolution multistage model specification are introduced. A multimodel specification formalism based on graph of models is suggested along with design precepts to enable flexible dynamic model updating. The notion of multisimulation is introduced to enable exploratory simulation using various types of multimodels.

Cognitive complexity and dynamic personality in agent simulation

Infohabitants of the connected information systems include individuals, organizations, smart appliances, smart buildings, and other smart systems, as well as virtual entities acting on their behalf. They can best be represented by software agents. Hence, realistic cognitive abilities of software agents such as influence of personality to decision making and problem solving is of practical computational importance. In this article, two characteristics are added to software agents with personality: dynamic personality and the relationships of personality trait openness with both problem solving ability and cognitive complexity. The last characteristic of openness leads to its impact to dynamic modification of problem solving ability. In this article, an implementation of a fuzzy agent with personality is realized in Java environment to show personality descriptors, personality factors, personality style, and problem solving success consequently. Furthermore, a prototype system is presented to update personality facets and respective personality trait openness which can affect problem solving ability.

GEST — A Modelling and Simulation Language Based on System Theoretic Concepts

GEST is the first model and simulation specification language. Specifications of the model and the experiment are totally separated. The modelling world view is based on the axiomatic system theory of Wymore which provides an excellent basis for simulation modelling and symbolic model processing. This chapter has two aims: 1) To present the GEST language and the robust and rich modelling paradigm it provides even for non-simulation application areas, as well as 2) to foster design and development of other GEST-like modelling and simulation languages which would provide other modelling formalisms within comprehensive modelling and simulation systems.

Model-Based Activities: A Paradigm Shift

The aim of this chapter is to explore the possibilities to place simulation in a central position for several scientific disciplines. The following topics are discussed: 1) A proposed shift of paradigm in simulation, 2) Fundamental elements of a simulation study, 3) Models and behavior, 4) Synergies of simulation, software engineering, artificial intelligence, and general system theories, 5) Elements of a model-based simulation software system, 6) Knowledge-based modelling and simulation systems, 7) Highlights of desirable research directions in simulation methodology and software.

Intelligent agents, simulation, and gaming

Artificial intelligence and intelligent agents are sources of synergy for simulation and computer-based games. They support striking realism of the physical environment and provide unique opportunities for learning and complex operations. This articles purpose is to explore the relationship of software agents to simulation and games. This includes agents with advanced cognitive abilities (introspection, perception, anticipation, and understanding) as well as those representing personality, emotion, and cultural aspects of individuals and societies including issues. A recent special issue of Simulation: Transactions of the Society for Modeling and Simulation International on agent-directed simulation (ADS) is introduced. As a prelude to its presentation, the promising synergy of artificial intelligence, simulation, and gaming is elaborated on. A unifying paradigm for the synergy of agents and simulation and gaming—namely, ADS—is presented. It includes agent simulation, agent-supported simulation, and agent-based simulation. Also, two different usages of the term agent-based simulation are clarified.