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This tutorial introduces concepts for modeling small unit combat as complex adaptive systems (CAS). It begins with a “human-centric” view of the individual combatant and small unit operations,which incorporates the concept of the individual as an integrated weapon system, the Warrior System. It addresses representation of situation awareness/situation understanding (SA/SU), and “soft” factors - morale,...
In this paper we discuss verification and validation of simulation models. Four different approaches to deciding model validity are described; two different paradigms that relate verification and validation to the model development process are presented; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are discussed;...
The initial transient is an unavoidable issue when estimating parameters of steady-state distributions. We discuss contexts and factors that affect how the initial transient is handled, provide a bibliography (from the system simulation literature), discuss criteria for evaluating initial-transient algorithms, arguing for focusing on the mean squared error (mse). We discuss the MSER statistic, showing...
Today, due to exciting developments in advanced computing techniques and technologies, many scientists can now make use of dedicated high speed networks and high performance computing. This so-called `e-Science' in enabling scientist across many fields to work together in global virtual research communities. What do these advancements mean for modeling and simulation? This advanced tutorial instigates...
This paper proposes an open-source algorithm for simulation optimization. The intent is to permit many who use a variety of simulation software codes to be able to apply the proposed methods using an MS Excel-Visual Basic interface. First, we review selected literature on simulation optimization and its usefulness. Then, we briefly discuss methods that are commonly used for simulation optimization...
There is a growing body of knowledge describing the economic and social challenge faced by the United States because of the small (14%) and decreasing number of students pursuing Science, Technology, Engineering, and Mathematics (STEM) majors. We propose a simple two-period, agent-based simulation based on social impact theory to predict the % yield of STEM majors. The model indicates that changes...
To provide a broader education for Operational Research PhD students in the UK, the Engineering and Physical Sciences Research Council funds the National Taught Course Centre for Operational Research (NATCOR). This is an initiative led by six UK universities and includes a one-week, residential simulation module taught for the first time in July 2009. We describe the background to NATCOR, summarize...
To graduate students accustomed to working with the numerical solution of partial differential equations using finite difference, finite elements, spectral methods, etc. where time generally progresses in evenly-spaced small intervals, switching paradigms to a discrete-event simulation environment is not only counterintuitive but is also difficult. The SimCenter at the University of Tennessee Chattanooga...
Ambassador agents represent simulation services that are candidates to contribute to the solution of a problem. They need to know and express enough about the simulations to negotiate with other ambassador agents if the represented simulation systems can be composed to contribute to the solution. A formal approach to simulation interoperability based on set theory and date modeling theory was developed...
Agent-based simulation (ABS) is a recent modeling technique that is being widely used in modeling complex social systems. Forrester's System Dynamics (SD) is another longstanding technique for modeling social systems. Several classical models of systems, such as the Kermack-McKendrick model of epidemiology, the Lotka-Volterra equations for modeling predator-prey relationships, and the Bass model for...
While eigenvalue elasticity analysis can offer insights into System Dynamics model behavior, such analysis is complicated, unwieldy and infeasible for larger models due to superlinear growth of the number of eigenvalue-parameter as the number of stocks rises. To overcome these difficulties, we develop a summary function elasticity analysis method, which aids in analyzing the impact of a parameter...
Hierarchical component based modeling and simulation holds great promise, especially in terms of modeling efficiency and model reuse. However, in practice, the approach has not yet lived to its potential. After a diagnosis of this state of affairs, a solution inspired from model driven engineering is proposed. The basic architecture of the framework is explained, based on meta-models, models, and...
This paper presents a broad perspective on traffic flow modeling at a spectrum of four scales. Modeling objectives and model properties at each scale are discussed and existing efforts are reviewed. In order to ensure modeling consistency and provide a microscopic basis for macroscopic models, it is critical to address the coupling among models at different scales, i.e. how less detailed models are...
Verification and validation (V&V) techniques are used in agent-based modeling (ABM) to determine whether the model is an accurate representation of the real system. Docking is a form of V&V that tries to align multiple simulation models. In a previous paper, we described the docking process of an ABM that simulates the life cycle of Anopheles gambiae. Results showed that the implementations...
Most modeling and simulation approaches applied in cell biology assume a homogeneous distribution of particles in space, although experimental studies reveal the importance of space to understand the dynamics of cells. There are already numerous spatial approaches focusing on the simulation of cells. Recently, they have been complemented by a set of spatial modeling languages whose operational semantics...
Simulation modeling in systems biology embarks on discrete event simulation only for cases of small cardinalities of entities and uses continuous simulation otherwise. Modern modeling environments like Bio-PEPA support both types of simulation within a single modeling formalism. Developing models for complex dynamic phenomena is not trivial in practice and requires careful verification and testing...
Many protein regulatory models contain chemical species best represented as having multiple states. Such models stem from the potential for multiple levels of phosphorylation or from the formation of multiprotein complexes. We seek to support such models by augmenting an existing modeling and simulation system. Interactions between multistate species can lead to a combinatorial explosion in the potential...
Distributed Denial of Service (DDoS) attacks on the Internet are used by attackers to be a nuisance, make a political statement (e.g. the 2009 attack against Estonia), or as a weapon of an Internet extortionist. Effective defense against these is a crucial study area, where advanced simulation techniques play a critical role, because of the enormous number of events involved. This paper considers...
Progress in programming paradigms and languages has over time influenced the way that simulation programs are written. Modern object-oriented, functional programming languages are expressive enough to define embedded Domain Specific Languages (DSLs). The Scala programming language is used to implement ScalaTion that supports several popular simulation modeling paradigms. As a case study, ScalaTion...
A novel pedestrian behavior model is proposed, which integrates 1) Extended Decision Field Theory (EDFT) for tactical level human decision-making, 2) Social Force model (SFM) to represent physical interactions and congestions among the people and the environment, and 3) dynamic planning algorithm involving AND/OR graphs. Furthermore, the Social Force model is enhanced with the vision of each individual,...
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