Simulation, Computer Approach

Monte Carlo Simulation

In a Monte Carlo simulation, values for uncertain variables are generated by the computer to reproduce information found in the real world. Named for the city of Monte Carlo, Monaco (where the primary attractions are games of chance at gambling casinos), a Monte Carlo simulation generates data pseudorandomly to explore hypothesized models. Much like the random behavior in games of chance, a Monte Carlo simulation selects values at random to simulate a variable. For example, when you roll a die, you know that a number from one to six will come up, but you don't know what number will come up for any particular roll. In much the same way, a Monte Carlo simulation works by first defining the possible values that simulated data can take as the same values found in the real world and then using that definition to generate random numbers. In this way, any number of variables that have a known range of values but an uncertain value for any particular time or event (e.g., interest rates, staffing needs, stock prices, inventory, phone calls per minute) can be modeled. In a typical Monte Carlo simulation, behavioral processes are entirely simulated by the computer.

Microworld Simulation

Microworld simulations have a higher level of realism. Microworld simulations are complex, computergenerated situations used in controlled experiments that are designed to study decision making. Microworld simulations represent a compromise between experimental control and realism and enable researchers to conduct experimental research within a dynamic, complex decision-making situation. In a typical microworld simulation, the situation is generated with a moderate degree of fidelity and behavioral processes are examined as humans navigate through it. The simulation is typically only unidimensional—that is, participants are instructed to make decisions that are cognitively complex but that do not invoke a range of senses (e.g., visual, aural, olfactory, tactile, and proprioceptive).

Virtual Reality Simulation

At the most realistic level, a virtual reality (VR) simulation is defined as a computer-simulated, multisensory environment in which a perceiver—the user of the VR computer technology—experiences telepresence. Telepresence is defined as feeling present in an environment that is generated by a communication medium such as a computer. In the context of VR, telepresence occurs when the VR user loses awareness of being present at the site of the human–computer interface and instead feels present or fully immersed in the VR environment. Thus, a successful VR simulation reproduces the experience of reality with a high degree of accuracy so that behavioral processes can be examined as humans navigate through the simulated environment. The simulation is typically multidimensional—that is, the best VR simulations attempt to invoke the full range of participants' senses (i.e., visual, aural, olfactory, tactile, and proprioceptive).

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