8.18. Randomness

| Chapter 8: Change |

| 8.18. Randomness

Sometimes we want to introduce random behaviour into play. We usually do this by generating random values, and then acting differently depending on what they are. The following:

> a random number from 2 to 5

produces, as it suggests, a random number drawn from the choices 2, 3, 4 or 5, each of which is equally likely to come up. In fact, this isn't limited to numbers:

a random (name of kind) between (arithmetic value) and (arithmetic value) ... value
or: a random (name of kind) from (arithmetic value) to (arithmetic value) ... value
or: a random (name of kind) between (enumerated value) and (enumerated value) ... value
or: a random (name of kind) from (enumerated value) to (enumerated value) ... value

This phrase produces a uniformly random value in the range given. Examples: a random number from 10 to 99 a random time from 2:31 PM to 2:57 PM If we make a new kind of value: A cloud pattern is a kind of value. The cloud patterns are cumulus, altocumulus, cumulonimbus, stratus, cirrus, nimbus, nimbostratus. then we can also take random values from it: a random cloud pattern between stratus and nimbus which has three possible outcomes, all equally likely.

We can also use random conditions:

if a random chance of (number) in (number) succeeds:

This condition is true X/Yths of the time, where X and Y are the numbers. Example: if a random chance of 2 in 3 succeeds, ... Here is a rule which applies only 15% of the time: Instead of waiting when a random chance of 15 in 100 succeeds: ...

Testing IF which makes random choices can be rather frustrating, because a problem showing up on one attempt may not show up on another. We can get around this by making use of the fact that computers do not actually generate true randomness, but instead make a sequence of apparently random numbers by applying a complicated formula to each one in order to make the next. The starting point is a number called the "seed", because the next choice grows out of it.

seed the random-number generator with (number)

This phrase changes the seed number as specified. Any random numbers generated after that depend only on the seed. Example: the following sentence will "fix" the process of generating these random numbers so that they are not random at all - the same sequence of random numbers will be produced on each run. When play begins, seed the random-number generator with 1234. The seed value "1234" can be anything positive; a different sequence of random numbers will be produced for each different seed value. A seed value of 0 restores the RNG to properly random behaviour again.

Alternatively, it's possible the "fix" the RNG by clicking the "Make random outcomes predictable when testing" option on the Settings panel. This makes the behaviour predictable whenever the game is played within Inform, but (unlike the rule above) has no effect on the story file once released.

129
| Example Do Pass Go A pair of dice which can be rolled, and are described with their current total when not carried, and have individual scores when examined. |
RB

130
| Example Lanista 1 Very simple randomized combat in which characters hit one another for a randomized amount of damage. |
RB

131
| Example Weathering The automatic weather station atop Mt. Pisgah shows randomly fluctuating temperature, pressure and cloud cover. |
RB

"Weathering" A cloud pattern is a kind of value. The cloud patterns are cumulus, altocumulus, cumulonimbus, stratus, cirrus, nimbus, nimbostratus. The Mount Pisgah Station is a room. "The rocky peak of Mt. Pisgah (altitude 872m) is graced only by an automatic weather station. The clouds, close enough almost to touch, are [a random cloud pattern]. Temperature: [a random number from 7 to 17] degrees, barometric pressure: [950 + a random number from 0 to 15] millibars." Test me with "look / look / look".

132
| Example Uptown Girls A stream of random pedestrians who go by the player. |
RB

Previous | Contents | Next