# An Introduction to Computer Simulation A computer simulation also known as a computer model or a computation model is a computer model that principally is meant to imitate an abstract model of a particular given system. Many natural system are conjured up from computer simulation e.g. in computational physics, chemistry and biology. Also in human Tertiary Sector In Indonesia system such as economical, psychological, sociological models and many other social sciences models. Basically, simulations are used to give a visible idea of a new technology, and further estimate the performance and speed of a system which might be difficult to do with use of analytical approaches.
Computer simulation involve generation of inputs from simulated objects e.g. flight simulators which run modeled items and at the same time an actual flight software to aid better understanding to the users. There are many different types of computer simulations, classified according to independent attributes, which include;
1. Stochastic or deterministic simulations; in this type of simulation, the next event is determined by ordering an array of the rates of all possible changes followed by taking a cumulative sum of the same array. The cell containing the number R (total event rate) is taken. This further makes a discrete cumulative probability distribution in which the next event can be chosen by picking a random number z ~U (0.R) and thus get the first event such that z is less than the rate associated with the event.
2. Continuous or discrete simulation model: Discrete event simulation manages events according to time e.g. number of cars arriving and leaving a petrol station at a particular time interval. The model maintains a queue of events in accordance with the set criterion. The simulator gets instruction from the queue and triggers new events as the previous ones are being processed. Most computers and fault-free simulation use this kind. On the other hand, continuous dynamic simulation is used where the state changes all the time e.g. the water level in a tank with inflows and outflows might keep on changing every time. It basically, performs differential equations. The model solves all the equations and uses the processed numbers to change the output of the final simulation. This kind is used in flight simulation, chemical modeling, car-race games and also electric circuit simulation.
3. Steady- state or dynamic simulation: this kind uses equations that show relationship between variables in the system and further gives an equilibrium state of the modeled system. For example steady state simulation can be used in pipeline aided simulations
4. Distributed simulation: this kind run on a network of linked computers via the internet. Simulations are dispersed to host computers and there are set protocols for this i.e. the Aggregate Level Simulation Protocol (ALSP), Distributed Interactive Simulation (DIS) and also the High Level Architecture (HLA).
5. Agent-based distribution: this is a special type of discrete type simulation which doesn’t rely on equations, but basically represented formally. In this independent entities like molecules, consumers, Porter’S Five Forces Starbucks trees. Cells e.t.c. are represented directly rather than the content they hold. The agent’s state is updated from time to time by looking at the set of rules and behaviors underlying such elements.