4 ms·

random and uniform are different things. a PRNG isn't "too random", that doesn't make sense. If it's too uniform, sample from other distributions, but to do so

by eterm 13y ago

random and uniform are different things. a PRNG isn't "too random", that doesn't make sense. If it's too uniform, sample from other distributions, but to do so usually requires taking output from a PRNG. Indeed using the inverse CDF of any distribution is a map from (0,1) to the desired sample space, following the distribution. As for which PRNG for RPG games, MT is very good because while it isn't cryptographically secure, it otherwise has a very long period and delivers very nicely distributed numbers as well as being very fast. For non-crypto applications such as monte-carlo, there's little reason to use much else.

Jach 13y ago
By "too random" I mean that for games, one often wants "predictable randomness" rather than unpredictable randomness, and a stock PRNG or MT can be too unpredictable. (Which is generally good, but not always for games. Or for candy; the colors of M&M's aren't distributed equally.) Picking your random values from a distribution is one way to make them predictable and more life-like. e.g. if you have a target shooting AI, using a built-in rand() function to select an angle and radius on the target is probably okay for the angle, but using it on the radius will give you a bad-looking spread. Whereas a Gaussian-selected radius will look more natural with most of the shots clustered close to the center, and it lets you easily fine-tune the AI's accuracy by adjusting parameters of the Gaussian. Alternatively, some sets of random values don't look random to humans, so as a game developer you might need to tweak it and make it appear more random to the player. e.g. these are some truly random bits from Hotbits (not a PRNG: https://www.fourmilab.ch/hotbits/secure_generate.html https://www.fourmilab.ch/hotbits/secure_generate.html): '001101010011001011001000010100011010011111000001111101010011000111010000111000001011111000111011'. My pattern-matching human brain is annoyed by runs longer than 3 or 4 times, and patterns like 000111 and 111000. If you take time to filter out 'annoyances' you can make the player like your game more, and if you're careful you can do it without decreasing the entropy bits per byte too much.

by eterm 13y ago

Jach 13y ago

By "too random" I mean that for games, one often wants "predictable randomness" rather than unpredictable randomness, and a stock PRNG or MT can be too unpredictable. (Which is generally good, but not always for games. Or for candy; the colors of M&M's aren't distributed equally.) Picking your random values from a distribution is one way to make them predictable and more life-like. e.g. if you have a target shooting AI, using a built-in rand() function to select an angle and radius on the target is probably okay for the angle, but using it on the radius will give you a bad-looking spread. Whereas a Gaussian-selected radius will look more natural with most of the shots clustered close to the center, and it lets you easily fine-tune the AI's accuracy by adjusting parameters of the Gaussian. Alternatively, some sets of random values don't look random to humans, so as a game developer you might need to tweak it and make it appear more random to the player. e.g. these are some truly random bits from Hotbits (not a PRNG: https://www.fourmilab.ch/hotbits/secure_generate.html https://www.fourmilab.ch/hotbits/secure_generate.html): '001101010011001011001000010100011010011111000001111101010011000111010000111000001011111000111011'. My pattern-matching human brain is annoyed by runs longer than 3 or 4 times, and patterns like 000111 and 111000. If you take time to filter out 'annoyances' you can make the player like your game more, and if you're careful you can do it without decreasing the entropy bits per byte too much.