Simulación

Una simulación es imitar algo real, un estado de asuntos o un proceso. El acto de simular algo generalmente requiere representar ciertas características claves o comportamiento de un sistema físico o abstracto escogido.

Una simulación se usa en muchos contextos, tales como una simulación de tecnología para mejorar el desempeño, ingeniería de seguridad, pruebas experimentales, entrenamiento, educación y juegos de videos. Simuladores de entrenamiento incluyendo simuladores de vuelo para entrenamiento de pilotos para que tengan una experiencia realista. La simulación además se utiliza para el modelaje científica de los sistemas naturales o los sistemas humanos para poder ganar una visión sobre su funcionamiento. En las palabras de la Enciclopedia de Ciencia Computacional, "diseño de un modelo de un sistema real o imaginario y llevar a cabo experimentos con ese modelo." La simulación puede ser utilizado para mostrar los efectos reales eventuales de condiciones y cursos de acción alternativas. Una simulación también se utiliza cuando un sistema real no puede ser desarrollado, porque puede ser no accesible, o peligroso o no aceptable para usar, o está siendo diseñado pero no todavía construido, o sencillamente no existe.

Los temas claves en la simulación incluyen adquisición de información de fuentes validos sobre la selección relevante de características y comportamientos claves, y el uso de aproximaciones y presunciones simplificantes entre la simulación, y fidelidad y validez de los resultados de la simulación.

Clasificación y terminología

Históricamente, las simulaciones utilizadas en diferentes campos fueron desarrollados en gran parte de manera independiente, pero los estudios del siglo XX de teoría de sistemas y cibernética, combinada con un uso cada vez mayor de computadores en todos los campos han resultado en alguna unificación y una vista más sistemática del concepto.

Simulación física se hace referencia a simulación en dónde los objetos físicos están sustituidos para la cosa real. Estos objetos físicos frecuentemente están escogidos porque son más pequeños o baratos que el objeto o sistema actual.

Simulación interactiva es un tipo especial de simulación física, frecuentemente referida como un humano en el ciclo simulación, en dónde las simulaciones físicas incluyen operadores humanos, tales como un simulador de vuelos o de conducción.

Con simulaciones de un humano en el ciclo se puede incluir una simulación de computador como un ambiente sintético.<ref name="environment">Grupo Thales define un ambiente sintético como "contraparte a los modelos simulados de sensores, plataformas y otros objetos activos" para "la simulación de factores externas que los afecta"[1] mientras que otros vendores utilizan el termino para lo más visual, simuladores de "realidad virtual"[2].</ref>

Simulación en la educación y capacitación

Una simulación se utiliza extensivamente para fines educativas. Se utiliza frecuentemente como manera de hipermedios adaptivos.

La simulación se utiliza con frecuencia en la capacitación de personal civil y militar.<ref>Para una perspectiva académica sobre los simuladores de capacitación, ver Towards Building an Interactive, Scenario-based Training Simulator, para aplicación médica Medical Simulation Training Benefits tal como se presenta por parte de vendores de simuladores y para práctica militar A civilian's guide to US defense and security assistance to Latin America and the Caribbean publicado por el Centro para Política Internacional.</ref> Esto oucrre usualmente cuando está prohibitivamente caro o sencillamente demasiado peligroso permitir a los capacitados utilizar los equipos verdaderos en el mundo real. En tales situaciones, gastarán tiempo aprendiendo lecciones valiosos en un ambiente virtual "seguro" sin embargo viviendo una experiencia cercana a la vida real (o por lo menos así es el objetivo). Frecuentemente la conveniencia es permitir errores durante el entrenamiento para un sistema de seguridad crítica. Por ejemplo, en simSchool los profesores practican gerencia de una aula y técnicas de enseñanza sobre estudiantes simulados, evitando "aprendiendo en el trabajo" que dañaría los estudiantes reales. Existe una distinción, sin embargo, entre las simulaciones utilizadas en el entrenamiento y la simulación instruccional.

Simulación de entrenamiento típicamente está dividido en tres categorías: <ref>Clasificación utilizado por la Oficinaa de Modelaje y Simulación de Defensa.</ref>

• simulación "en vivo" (en donde jugadores actuales utilizan sistemas genuinos en un ambiente real);
• simulación "virtual" (en donde jugadores actuales utilizan sistemas simulados en un ambiente sintético <ref name="environment"/>), o
• simulación "constructiva" (en dónde jugadores virtuales utilizan sistemas simulados en un ambiente sintético). La simulación constructiva frecuentemente se refiere como "juego de guerra" dado que parece a juegos de guerra de mesa en dónde los jugadores mandan ejércitos de soldados y equipos que mueven por la mesa.

En una prueba estandardizada, simulaciones "en vivo" aveces se llaman "alta-fidelidad", produciendo "muestras de desempeño probable", a diferencia de "baja fidelidad", simulacioens de "lápiz y papel" produciendo "señales de posible desempeño",<ref>"High Versus Low Fidelity Simulations: Does the Type of Format Affect Candidates' Performance or Perceptions?"</ref> pero las distinciones entre fidelidad alta, moderada y baja, dependen en el contexto de una comparación particular.

Las simulaciones en la educación son frecuentemente parecidos a simulaciones de entrenamiento. Se enfoquen en tareas específicas. El termino 'micromundo' se utiliza para referirse a simulaciones educacionales que modelan algún concepto abstracto en lugar de simular un objeto o ambiente realista, o en algunos casos modelan un ambiente del mundo real de una manera simplista para así permitir un aprendiz desarrollar un entendimiento de los conceptos claves. Normalmente, un usuario puede crear algún tipo de construcción entre un micromundo que compartará de una manera consistente con los conceptos siendo modelados. Seymour Papert fue entre los primeros de abogar el valor de los micromundos, y el lenguaje de programación Logo como ambiente de programación desarrollado por Papert es entre los micromundos más famosos. Como otro ejemplo, el Premio de Retos Globales, un sitio de aprendizaje STEM, utiliza simulaciones micromundo para enseñar conceptos de la ciencia relacionadas con el calentamiento global y el futuro de la energía. Otros proyectos para simulación en educación son Física de Fuente Abierta, NetSim, etc.

Simulaciones sociales pueden ser utilizados en aulas de clase de las ciencias sociales para poder ilustrar procesos sociales y políticos en la antropología, economía, historía, ciencias políticas, o sociología, típicamente al nivel de colegio o universidad. Estos pueden, por ejemplo, tomar la forma de simulaciones de cívica, en dónde los participantes asumen papeles en una sociedad simulada, o relaciones internacionales, en dónde participantes entran en negociaciones, la formación de alianzas, comercio, diplomacia y el uso de la fuerza. Tales simulaciones pueden basarse en sistemas políticas ficticias, o sobre eventos históricos.

Uso de simulaciones sociales en Agencias

En años recientes, se ha empezado aumentar el uso de simulaciones sociales para la capacitación de personal en agencias de ayuda y desarrollo. La simulación Carana, por ejemplo, fue desarrollado inicialmente por el Programa de las Naciones Unidas para el Desarrollo y ahora se usa en una forma muy revisada por el Banco Mundial para entrenar sus empleados sobre cómo tratarse con países afectados por conflicto.<ref>"Carana," at 'PaxSims' blog, 27 January 2009</ref> En respuesta a desastres, en paises con una presencia de las Naciones Unidas, se recomienda hacer un Ejercicio de Simulación Inter-Agencial con cierta frecuencia para estar preparados.

Entrenamiento de Simulación y Preparación para Desastres

Entrenamiento de simulación ha vuelto un método para preparar la gente para los desastres. Las simulaciones pueden replicar situaciones de emergencia y monitorear sobre cómo los aprendices responden gracias a una experiencia parecida a la vida real. Simulaciones de preparación para desastres pueden involucrar entrenamiento sobre cómo responder a ataques terroristas, desastres naturales, brotes de pandemia u otras emergencias que amenazan la vida.

One organization that has used simulation training for disaster preparedness is CADE (Center for Advancement of Distance Education). CADE<ref>CADE- http://www.uic.edu/sph/cade/</ref> has used a video game to prepare emergency workers for multiple types of attacks. As reported by News-Medical.Net, ”The video game is the first in a series of simulations to address bioterrorism, pandemic flu, smallpox and other disasters that emergency personnel must prepare for.<ref>News-Medical.Net article- http://www.news-medical.net/news/2005/10/27/14106.aspx</ref>” Developed by a team from the University of Illinois at Chicago (UIC), the game allows learners to practice their emergency skills in a safe, controlled environment.

The Emergency Simulation Program (ESP) at the British Columbia Institute of Technology (BCIT), Vancouver, British Columbia, Canada is another example of an organization that uses simulation to train for emergency situations. ESP uses simulation to train on the following situations: forest fire fighting, oil or chemical spill response, earthquake response, law enforcement, municipal fire fighting, hazardous material handling, military training, and response to terrorist attack <ref name="straylightmm.com">http://www.straylightmm.com/</ref> One feature of the simulation system is the implementation of “Dynamic Run-Time Clock,” which allows simulations to run a 'simulated' time frame, 'speeding up' or 'slowing down' time as desired”<ref name="straylightmm.com"/> Additionally, the system allows session recordings, picture-icon based navigation, file storage of individual simulations, multimedia components, and launch external applications.

At the University of Québec in Chicoutimi, a research team at the outdoor research and expertise laboratory (Laboratoire d'Expertise et de Recherche en Plein Air - LERPA) specializes in using wilderness backcountry accident simulations to verify emergency response coordination.

Instructionally, the benefits of emergency training through simulations are that learner performance can be tracked through the system. This allows the developer to make adjustments as necessary or alert the educator on topics that may require additional attention. Other advantages are that the learner can be guided or trained on how to respond appropriately before continuing to the next emergency segment—this is an aspect that may not be available in the live-environment. Some emergency training simulators also allows for immediate feedback, while other simulations may provide a summary and instruct the learner to engage in the learning topic again.

In a live-emergency situation, emergency responders do not have time to waste. Simulation-training in this environment provides an opportunity for learners to gather as much information as they can and practice their knowledge in a safe environment. They can make mistakes without risk of endangering lives and be given the opportunity to correct their errors to prepare for the real-life emergency.

Engineering, technology or process simulation

Simulation is an important feature in engineering systems or any system that involves many processes. For example in electrical engineering, delay lines may be used to simulate propagation delay and phase shift caused by an actual transmission line. Similarly, dummy loads may be used to simulate impedance without simulating propagation, and is used in situations where propagation is unwanted. A simulator may imitate only a few of the operations and functions of the unit it simulates. Contrast with: emulate.<ref name="FS1037C">Federal Standard 1037C</ref>

Most engineering simulations entail mathematical modeling and computer assisted investigation. There are many cases, however, where mathematical modeling is not reliable. Simulation of fluid dynamics problems often require both mathematical and physical simulations. In these cases the physical models require dynamic similitude. Physical and chemical simulations have also direct realistic uses,<ref>Plantilla:Cite journal</ref> rather than research uses; in chemical engineering, for example, process simulations are used to give the process parameters immediately used for operating chemical plants, such as oil refineries.

Payment and Securities Settlement System Simulations

Simulation techniques have also been applied to payment and securities settlement systems. Among the main users are central banks who are generally responsible for the oversight of market infrastructure and entitled to contribute to the smooth functioning of the payment systems.

Central Banks have been using payment system simulations to evaluate things such as the adequacy or sufficiency of liquidity available ( in the form of account balances and intraday credit limits) to participants (mainly banks) to allow efficient settlement of payments.<ref>Leinonen (ed.): Simulation studies of liquidity needs, risks and efficiency in payment networks (Bank of Finland Studies E:39/2007) Simulation publications</ref><ref>Neville Arjani: Examining the Trade-Off between Settlement Delay and Intraday Liquidity in Canada's LVTS: A Simulation Approach (Working Paper 2006-20, Bank of Canada) Simulation publications</ref> The need for liquidity is also dependent on the availability and the type of netting procedures in the systems, thus some of the studies have a focus on system comparisons.<ref>Johnson, K. - McAndrews, J. - Soramäki, K. 'Economizing on Liquidity with Deferred Settlement Mechanisms' (Reserve Bank of New York Economic Policy Review, December 2004)</ref>

Another application is to evaluate risks related to events such as communication network breakdowns or the inability of participants to send payments (e.g. in case of possible bank failure).<ref>H. Leinonen (ed.): Simulation analyses and stress testing of payment networks (Bank of Finland Studies E:42/2009) Simulation publications</ref> This kind of analysis fall under the concepts of Stress testing or scenario analysis.

A common way to conduct these simulations is to replicate the settlement logics of the real payment or securities settlement systems under analysis and then use real observed payment data. In case of system comparison or system development, naturally also the other settlement logics need to be implemented.

To perform stress testing and scenario analysis, the observed data needs to be altered, e.g. some payments delayed or removed. To analyze the levels of liquidity, initial liquidity levels are varried. System comparisons (benchmarking)or evaluations of new netting algorithms or rules are performed by running simulations with a fixed set of data and wariating only the system setups.

Inference is usually done by comparing the benchmark simulation results to the results of altered simulation setups by comparing indicators such as unsettled transactions or settlement delays.

Space Shuttle Countdown Simulation

Archivo:KSCFiringroom1.jpg

Firing Room 1 configured for space shuttle launches

Simulation is used at Kennedy Space Center (KSC) to train and certify Space Shuttle engineers during simulated launch countdown operations. The Space Shuttle engineering community participates in a launch countdown integrated simulation before each shuttle flight. This simulation is a virtual simulation where real people interact with simulated Space Shuttle vehicle and Ground Support Equipment (GSE) hardware. The Shuttle Final Countdown Phase Simulation, also known as S0044, involves countdown processes that integrate many of the Space Shuttle vehicle and GSE systems. Some of the Shuttle systems integrated in the simulation are the Main Propulsion System, Main Engines, Solid Rocket Boosters, ground Liquid Hydrogen and Liquid Oxygen, External Tank, Flight Controls, Navigation, and Avionics.<ref>Sikora, E.A. (2010, July 27). Space Shuttle Main Propulsion System expert, John F. Kennedy Space Center. Interview.</ref> The high-level objectives of the Shuttle Final Countdown Phase Simulation are:

• To demonstrate Firing Room final countdown phase operations.
• To provide training for system engineers in recognizing, reporting and evaluating system problems in a time critical environment.
• To exercise the launch teams ability to evaluate, prioritize and respond to problems in an integrated manner within a time critical environment.
• To provide procedures to be used in performing failure/recovery testing of the operations performed in the final countdown phase.<ref>Shuttle Final Countdown Phase Simulation. National Aeronautics and Space Administration KSC Document # RTOMI S0044, Revision AF05, 2009.</ref>

The Shuttle Final Countdown Phase Simulation takes place at the Kennedy Space Center Launch Control Center Firing Rooms. The firing room used during the simulation is the same control room where real launch countdown operations are executed. As a result, equipment used for real launch countdown operations is engaged. Command and control computers, application software, engineering plotting and trending tools, launch countdown procedure documents, launch commit criteria documents, hardware requirement documents, and any other items used by the engineering launch countdown teams during real launch countdown operations are used during the simulation. The Space Shuttle vehicle hardware and related GSE hardware is simulated by mathematical models (written in Shuttle Ground Operations Simulator (SGOS) modeling language <ref>Shuttle Ground Operations Simulator (SGOS) Summary Description Manual. National Aeronautics and Space Administration KSC Document # KSC-LPS-SGOS-1000, Revision 3 CHG-A, 1995.</ref>) that behave and react like real hardware. During the Shuttle Final Countdown Phase Simulation, engineers command and control hardware via real application software executing in the control consoles – just as if they were commanding real vehicle hardware. However, these real software applications do not interface with real Shuttle hardware during simulations. Instead, the applications interface with mathematical model representations of the vehicle and GSE hardware. Consequently, the simulations bypass sensitive and even dangerous mechanisms while providing engineering measurements detailing how the hardware would have reacted. Since these math models interact with the command and control application software, models and simulations are also used to debug and verify the functionality of application software.<ref>Math Model Main Propulsion System (MPS) Requirements Document, National Aeronautics and Space Administration KSC Document # KSCL-1100-0522, Revision 9, June 2009.</ref>

Satellite Navigation Simulators

The only true way to test GNSS receivers (commonly known as Sat-Nav's in the commercial world)is by using an RF Constellation Simulator. A receiver that may for example be used on an aircraft, can be tested under dynamic conditions without the need to take it on a real flight. The test conditions can be repeated exactly, and there is full control over all the test parameters. this is not possible in the 'real-world' using the actual signals. For testing receivers that will use the new Galileo (satellite navigation) there is no alternative, as the real signals do not yet exist.

Communication Satellite Simulation

Modern satellite communications systems (SatCom) are often large and complex with many interacting parts and elements. In addition, the need for broadband connectivity on a moving vehicle has increased dramatically in the past few years for both commercial and military applications. To accurately predict and deliver high quality of service, satcom system designers have to factor in terrain as well as atmospheric and meteorological conditions in their planning. To deal with such complexity, system designers and operators increasingly turn towards computer models of their systems to simulate real world operational conditions and gain insights in to usability and requirements prior to final product sign-off. Modeling improves the understanding of the system by enabling the SatCom system designer or planner to simulate real world performance by injecting the models with multiple hypothetical atmospheric and environmental conditions.

Finance simulation

In finance, computer simulations are often used for scenario planning. Risk-adjusted net present value, for example, is computed from well-defined but not always known (or fixed) inputs. By imitating the performance of the project under evaluation, simulation can provide a distribution of NPV over a range of discount rates and other variables.

Simulations are frequently used in financial training to engage participates in experiencing various historical as well as fictional situations. There are stock market simulations, portfolio simulations, risk management simulations or models and forex simulations. Using these simulations in a training program allows for the application of theory into a something akin to real life. As with other industries, the use of simulations can be technology or case-study driven.

Flight simulation

Flight Simulation Training Devices (FSTD) are used to train pilots on the ground. In comparison to training in an actual aircraft, simulation based training allows for the training of maneuvers or situations that may be impractical (or even dangerous) to perform in the aircraft, while keeping the pilot and instructor in a relatively low-risk environment on the ground. For example, electrical system failures, instrument failures, hydraulic system failures, and even flight control failures can be simulated without risk to the pilots or an aircraft.

Instructors can also provide students with a higher concentration of training tasks in a given period of time than is usually possible in the aircraft. For example, conducting multiple instrument approaches in the actual aircraft may require significant time spent repositioning the aircraft, while in a simulation, as soon as one approach has been completed, the instructor can immediately preposition the simulated aircraft to an ideal (or less than ideal) location from which to begin the next approach.

Flight simulation also provides an economic advantage over training in an actual aircraft. Once fuel, maintenance, and insurance costs are taken into account, the operating costs of an FSTD are usually substantially lower than the operating costs of the simulated aircraft. For some large transport category airplanes, the operating costs may be several times lower for the FSTD than the actual aircraft.

Some people who use simulator software, especially flight simulator software, build their own simulator at home. Some people — in order to further the realism of their homemade simulator — buy used cards and racks that run the same software used by the original machine. While this involves solving the problem of matching hardware and software — and the problem that hundreds of cards plug into many different racks — many still find that solving these problems is well worthwhile. Some are so serious about realistic simulation that they will buy real aircraft parts, like complete nose sections of written-off aircraft, at aircraft boneyards. This permits people to simulate a hobby that they are unable to pursue in real life.

Automobile simulator

Archivo:Vehicle simulator.jpg

A soldier tests out a heavy-wheeled-vehicle driver simulator.

An automobile simulator provides an opportunity to reproduce the characteristics of real vehicles in a virtual environment. It replicates the external factors and conditions with which a vehicle interacts enabling a driver to feel as if they are sitting in the cab of their own vehicle. Scenarios and events are replicated with sufficient reality to ensure that drivers become fully immersed in the experience rather than simply viewing it as an educational experience.

The simulator provides a constructive experience for the novice driver and enables more complex exercises to be undertaken by the more mature driver. For novice drivers, truck simulators provide an opportunity to begin their career by applying best practice. For mature drivers, simulation provides the ability to enhance good driving or to detect poor practice and to suggest the necessary steps for remedial action. For companies, it provides an opportunity to educate staff in the driving skills that achieve reduced maintenance costs, improved productivity and, most importantly, to ensure the safety of their actions in all possible situations.

Marine simulators

Bearing resemblance to flight simulators, marine simulators train ships' personnel. The most common marine simulators include:

• Ship's bridge simulators
• Engine room simulators
• Cargo handling simulators
• Communication / GMDSS simulators
• ROV simulators

Simulators like these are mostly used within maritime colleges, training institutions and navies. They often consist of a replication of a ships' bridge, with operating desk(s), and a number of screens on which the virtual surroundings are projected.

Military simulations

Plantilla:Main Military simulations, also known informally as war games, are models in which theories of warfare can be tested and refined without the need for actual hostilities. They exist in many different forms, with varying degrees of realism. In recent times, their scope has widened to include not only military but also political and social factors (for example, the NationLab series of strategic exercises in Latin America.<ref>See, for example, United States Joint Forces Command "Multinational Experiment 4"</ref> Whilst many governments make use of simulation, both individually and collaboratively, little is known about the model's specifics outside professional circles.

Robotics simulators

Plantilla:Main A robotics simulator is used to create embedded applications for a specific (or not) robot without being dependent on the 'real' robot. In some cases, these applications can be transferred to the real robot (or rebuilt) without modifications. Robotics simulators allow reproducing situations that cannot be 'created' in the real world because of cost, time, or the 'uniqueness' of a resource. A simulator also allows fast robot prototyping. Many robot simulators feature physics engines to simulate a robot's dynamics.

Biomechanics simulators

Plantilla:Main A biomechanics simulator is used to analyze walking dynamics, study sports performance, simulate surgical procedures, analyze joint loads, design medical devices, and animate human and animal movement.

Plantilla:Main A neuromechanical simulator that combines biomechanical and biologically realistic neural network simulation. It allows the user to test hypotheses on the neural basis of behavior in a physically accurate 3-D virtual environment.

Sales process simulators

Plantilla:Main Simulations are useful in modeling the flow of transactions through business processes, such as in the field of sales process engineering, to study and improve the flow of customer orders through various stages of completion (say, from an initial proposal for providing goods/services through order acceptance and installation). Such simulations can help predict the impact of how improvements in methods might impact variability, cost, labor time, and the quantity of transactions at various stages in the process. A full-featured computerized process simulator can be used to depict such models, as can simpler educational demonstrations using spreadsheet software, pennies being transferred between cups based on the roll of a die, or dipping into a tub of colored beads with a scoop.<ref name="Selden 1997">Plantilla:Cite book</ref>

Simulation and games

Plantilla:Main Strategy games — both traditional and modern — may be viewed as simulations of abstracted decision-making for the purpose of training military and political leaders (see History of Go for an example of such a tradition, or Kriegsspiel for a more recent example).

Many other video games are simulators of some kind. Such games can simulate various aspects of reality, from business, to government, to construction, to piloting vehicles (see above).

Historical usage

Historically, the word had negative connotations:

However, the connection between simulation and dissembling later faded out and is now only of linguistic interest.<ref>South, in the passage quoted, was speaking of the differences between a falsehood and an honestly mistaken statement; the difference being that in order for the statement to be a lie the truth must be known, and the opposite of the truth must have been knowingly uttered. And, from this, to the extent to which a lie involves deceptive words, a simulation involves deceptive actions, deceptive gestures, or deceptive behavior. Thus, it would seem, if a simulation is false, then the truth must be known (in order for something other than the truth to be presented in its stead); and, for the simulation to simulate. Because, otherwise, one would not know what to offer up in simulation. Bacon’s essay Of Simulation and Dissimulation expresses somewhat similar views; it is also significant that Samuel Johnson thought so highly of South's definition, that he used it in the entry for simulation in his Dictionary of the English Language.</ref>

See also

• Dissimulation
• Emulator
• in silico
• Futures studies
• High-level emulation
• Lifelike experience
• List of discrete event simulation software
• List of computer simulation software
• Mathematical model
• Merger simulation

• Mining simulation
• Molecular dynamics
• Network Simulator
• Pharmacokinetics simulation
• Placebo
• Roleplay simulation
• Simulation language
• Similitude (model)
• Simulated reality
• Training Simulation
• Web based simulation

References

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Further reading

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• Roger D. Smith: Simulation Article, Encyclopedia of Computer Science, Nature Publishing Group, ISBN 978-0-333-77879-1.
• Roger D. Smith: "Simulation: The Engine Behind the Virtual World", eMatter, December, 1999.
• R. South (1688). "A Sermon Delivered at Christ-Church, Oxon., Before the University, Octob. 14. 1688: Prov. XII.22 Lying Lips are abomination to the Lord", pp. 519–657 in South, R., Twelve Sermons Preached Upon Several Occasions (Second Edition), Volume I, Printed by S.D. for Thomas Bennet, (London), 1697.
• Eric Winsberg (1999) Sanctioning Models: The epistemology of simulation, in Sismondo, Sergio and Snait Gissis (eds.) (1999), Modeling and Simulation. Special Issue of Science in Context 12.
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• James J. Nutaro, Building Software for Simulation: Theory and Algorithms, with Applications in C++. Wiley, 2010.

External links

• Bibliographies containing more references to be found on the website of the journal Simulation & Gaming.