What happens if the same seed value is always used for generating random numbers?
Seeding a pseudo-random number generator gives it its first “previous” value. Each seed value will correspond to a sequence of generated values for a given random number generator. That is, if you provide the same seed twice, you get the same sequence of numbers twice.
Can a random number generator be random?
Random number generators can be truly random hardware random-number generators (HRNGS), which generate random numbers as a function of current value of some physical environment attribute that is constantly changing in a manner that is practically impossible to model, or pseudorandom number generators (PRNGS), which …
Can a random number be generated by a seed?
The requirement specification shows a sample like this: The rand result is not directly given out, but used for other performance. I’d written the same code as above to generate a random number by a seed 3412. however, the result of the rest performance is totally different with sample.
How are pseudo random number generators used in real life?
These are a real help in real life! Virtually all “random” number generators implemented in computer languages are pseudo random number generators. This is because given a starting value (===> the seed) they will always provide the same sequence of pseudo random results.
What causes every machine to generate the same result?
Providing an identical seed value to different Random objects causes each instance to produce identical sequences of random numbers. but it doesn’t specify the implications of different versions etc. Heck, it doesn’t even state whether the x86 and x64 versions will give the same results.
How to generate a vector of random numbers?
One easy way is to add all numbers from 0-99 to a vector and shuffle it, then you can get as many (up to 100) non repeating random numbers as you require. and then copy it into a vector if necessary. srand number generator can give identical numbers. You could implement a solution which deletes duplicates not adding them to the vector.