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• The problem of random number generation is one of the most important issues related to the modeling of natural processes. This problem occurs also in various kinds of games and lotteries.
  The first methods of generating random numbers were based on the observation of a physical phenomenon - eg. the number of dots, which fell on the cubical dice. Other methods, which can be used to get random numbers are for example coin flip, or rotate the roulette wheel.
  
• Fast development of computers and constant growth of their computational capabilities allow to model and simulate various natural, increasingly more complex phenomena. In order to get a large number of random numbers, the methods used for gaming and gambling are too cumbersome - and therefore there was a need to find new, better methods of generating random numbers.
  
• Because computers work in deterministic manner, they are not very suitable to generate a truly unique sequences of random numbers. In situations where the randomness of the numbers generated is fundamental, the stochastic processes occurring in nature are applied, as these are unpredictable due to the laws of quantum physics such as radioactivity, thermal noise, or the radio noise.
  
• Human behaviour can also be a source of random numbers.
  The unpredictability of human behaviour is used in the random number generators used in cryptography - for example where it is very important to obtain an unpredictable number used as a seed for encryption algorithm.
  One of the ways to convert human activities to the sequence of random numbers is to ask him to perform random mouse movements or press random keys. The basis for the generated numbers can be a specific location of the mouse cursor or presses of particular keys on the keyboard, but also the time between successive events.
  
• There are many scenarios, when we need to generate random numbers without any human intervention and without the possibility of using "natural" source of random numbers (eg. microphone noise). So, scientists work on algorithms to generate such numbers.
  
• Such algorithms are usually based on some form of recursion, where the first value - often called seed - is either set as a fixed or taken from some other source. Seed value is often obtained from the real-time clock.
  
• Because computer works in deterministic manner, it's not able to generate a "real" random numbers. It also means that generated numbers - no matter what algorithm is used - will be repeated sooner or later. Getting a good random number generator would require periods not to happen. Due to this fact the random numbers generated by computer algorithm are called pseudo-random numbers.