I want to make characters in a game perform actions that are partially random but also influenced by preferences. For instance, if a character feels angry they have a higher chance of yelling than telling a joke. So I’m thinking about how to determine which action the character will take. Here are the ideas that have come to me.
Solution #1: Iterate over every possible action. For each action do a random roll, then add the preference value to that random number. The action with the highest value is the one the character takes.
Solution #2: Assign a range of numbers to an action, with more likely actions having a wider range. So, if the random roll returns anywhere from 1-5, the character will tell a joke. If it returns 6-75, they will yell. And so on.
Solution #3: Group all the actions and make a branching tree. Will they take a friendly action or a hostile action? The random roll (with preference values added) says hostile. Will they make a physical attack or verbal? The random roll says verbal. Keep going down the line until you reach the action.
Solution #1 is the simplest, but hardly efficient. I think Solution #3 is a little more complicated, but isn’t it more efficient?
Does anyone have any more insight into this particular problem? Is #3 the best solution? Is there a better solution?
#1 and #2 are simple but probably won’t scale well to more complicated behaviors. Behavior trees (#3) seem to be the preferred system in many games nowadays. You can find some presentations and notes on AiGameDev.com, e.g. http://aigamedev.com/open/coverage/paris09-report/#session3 and http://aigamedev.com/open/coverage/gdc10-slides-highlights/#session2 (the first one from Crytek is quite good)
You probably don’t need to worry about “efficiency” here in the sense of CPU usage, since this is very unlikely be a major bottleneck in your game. Reducing the amount of programmer/designer time needed to tweak the behavior is much more important.