Computer Simulations

In a computer simulation, a digital computer is used to trace the time evolution of a system, e.g., of the atmosphere of the Earth. Using a model, the computer calculates the values of variables such as air pressure for a series of times and thus obtains state descriptions of the system for those times. The outputs of computer simulations are often visualized using animations. If all goes well in the simulation, humans can learn from the outputs how the system under consideration evolves with time. Computer simulations became possible with the advent of the digital computer in the 1940s. They contrast with analog simulations, which do without a digital computer and are not considered in this entry. Among the first computer simulations were programs that were intended to trace the explosion of nuclear weapons and the evolution of the weather. Nowadays, the use of computer simulations is widespread, in particular in education and in research in the natural and social sciences. But not every use of the computer qualifies as computer simulation; for instance, the classification of images using neural networks does not count as computer simulation because no time evolution is traced. In philosophy, computer simulation is mainly discussed as a scientific practice or method. Accordingly, it is mostly philosophers of science who study computer simulation. Their focus has been on the epistemology of computer simulation: They study how computer simulations are embedded in, and change, the workings of science. The most important questions are: (1) How are computer simulations used in different disciplines and what kinds of tasks do they fulfill? (2) How are simulation results justified? (3) How can we explain how computer simulations achieve their tasks? Since answers to this question often relate computer simulation to other methods, e.g., experimentation, they also tell us what kind of method computer simulation is. (4) To what extent are computer simulations novel in science and what are the consequences for our philosophical picture of science? The last question is pressing because well-established positions in philosophy of science, e.g., falsificationism, Bayesianism, and Kuhn’s position, have been developed without reference to computer simulation. An additional important topic that has emerged in the philosophical discussion of simulations is their black box character. This trait is often labeled “epistemic opacity” and seems relevant for the question of how computer simulations can provide understanding. The current wave of interest in computer simulations started in the 1990s, although there were a few philosophical publications on the theme before that time. This bibliography covers this wave without going further back to the past. The focus is entirely on philosophical appraisals of simulations within science. The use of simulations as a tool within philosophy is largely bracketed.