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Most random sources are PRNG rather than 'true' random sources, and sometimes it's useful (for debugging, for analysis or just for interest) to be able to use a predictable pattern of otherwise random numbers. One way is to allow some way of 'seeding' the PRNG such that the order of the numbers it produces is the same each time, as we return the random function back to a known state. Or, by example, if I make 5 calls to the PRNG with seed value '0' and see the following: [5, 2, 9, 18, 4, ...] and that causes the agent I'm testing to do something utterly weird, so I want to re-run my agent to observe the effect in detail to debug it, and for that to happen, I need the same [5, 2, 9, 18, 4, ...] sequence, otherwise I'll be forced to run repeatedly until I observe the same glitch, so by re-seeding the PRNG to '0', it will then predictably return that sequence, rather than a new, random sequence. |