The Relationship Editor handles the tedious task of defining all the relationships among all the Actors. There are quite of few of these, and it can take a lot of work to fill in all the data, so the Relationship Editor also provides a few tools for easing your workload.

But first, we have to explain a few concepts. The core concept is the ActorAttribute. You learned about Attributes in Lesson 10. What we didn't tell you is that Attributes can be perceived by other Actors—and that these perceived values are not necessarily the same as the actual values.

Let's illustrate this with an example: imagine an Attribute called False_Honest, representing the integrity of an Actor. Rick's False_Honest value, as specified in the Actor Editor, is how False_HonestRick truly is. The pFalse_Honest value (the "perceived" False_Honest value) of Jane for Rick is how False_Honest Jane thinks Rick is (i.e., how much she trusts him). The cFalse_Honest is how sure she is of her perception. For example, if she knows only what's she has heard of him on the grapevine, cFalse_Honest will be low, but if she has direct experience of Rick's False_Honest (if, for example, she knows that he lied to her), then her cFalse_Honest will be higher.

This is important because, in drama, different people have differing estimates of others. Those differing estimates are the source of so much dramatic fodder, as people gossip about others. And these differing perceptions will be the source of some conflict themselves. Suppose, for example, that Francesca tells Jane that she thinks Rick is trustworthy (Rick's False_Honest value is high). Jane, however, believes that Rick is not trustworthy (Rick's False_Honest value is low). Jane will note the discrepancy between her existing estimation of Rick and what Francesca is telling her. Perhaps she will modify her estimation of Rick's False_Honest upwards. Perhaps she will decide that Francesca is lying. It depends on some other factors. You can see how our expert Laura Mixon handled this tricky problem in this portion of an Inclination script from her demonstration storyworld, ChitChat:

Tell re personality: tellee: contradict: Inclination

...

Blend of:

     1. I have a big diff in perception from you

     BAbsval of:

          BDifference of:

               CorrespondingPActorTrait of:

                    ReactingActor

                    This4Actor

                    This5ActorTrait

               Quantifier2BNumber of:

                    This6Quantifier

     2. I am certain I am right in my perception

     BInverse of:

          CorrespondingCActorTrait of:

               ReactingActor

               This4Actor

               This5ActorTrait

...

Going back to the Actor Editor, we can now understand the two concepts of Accordance and Weight. Accordance is how readily an Actor accords high values of the Attribute to others. Thus, if Jane has a high accordFalse_Honest, then she readily assumes that other Actors have high values of False_Honest—in other words, she's gullible. If she has a low value of accordFalse_Honest, then she's suspicious: she doesn't give people a high value of False_Honest unless they prove it to her.

False_HonestWeight is the degree to which an Actor desires to have high pFalse_Honest values—in other words, how much that Actor desires to be trusted. An Actor who is vain will have a high value of Ugly_AttractiveWeight; an Actor with a low value of Cowardly_BraveWeight doesn't care if other people think he's a coward.

There are three special variables that require your attention: familiarity, debt_Grace, and stranger_Kin. These are all BNumber variables. The first, familiarity, is useful for initializing p-values. Notice the little checkboxes next to each of the regular p-Attributes. If you check one of those, then you're telling SWAT "I'll fill in this value myself." But if you uncheck this box, then you're telling the Engine, "Fill it in automatically for me." The Engine will use the familiarity value along with the accordance value to calculate the p-value directly, so you don't have to. Here's the algorithm that the Engine uses:

        1. It starts off assuming that the p value is 0.00 (the most likely case)

        2. Then it biases it towards the actual value in proportion to the familiarity value.

        3. Lastly, it biases it up or down in proportion to the accord value

It's a big time-saver, and it yields good results in most cases. You'll want to use the manual override (checking the box) rarely.

When you use the automatic procedure by unchecking the checkbox, the c-value is the same thing as the familiarity value.

Next comes the debt_Grace value. Normally, you'll just initialize this to zero. It represents the idea of tanagadalang (if you're Indonesian) or an interpersonal kind of karma, or just the idea that "You owe me." We've found that it can be very handy in a lot of drama. Remember, it's not necessarily symmetric: two different Actors can have very different ideas of who owes whom.

Lastly, there's the stranger_Kin relationship. This is used to handle the dramatic relationship expressed in the adage "Blood is thicker than water." It can also be used to handle kinship based on marriage, adoption, and so on.  It's a little odd, though, in that 0.0, which normally expresses the "average" value, in this case should reflect something a little more than that.

Depending on the range and importance of kinship in your storyworld, you can set the Actors' relationships accordingly. For instance, in a tight-knit family drama, you may want to set 0.0 as cousins. In a storyworld about racial relations or the clash between two cultures, 0.0 might represent people of the same clan or ethnicity. In storyworld of a first contact with extraterrestrials, 0.0 might mean two Actors are simply of the same species!

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  This tutorial by Storytron, Inc. is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.