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Variation, Chance and Randomness
by Glenn Storm on 01/12/10 09:15:00 am

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The following blog post, unless otherwise noted, was written by a member of Gamasutra’s community.
The thoughts and opinions expressed are those of the writer and not Gamasutra or its parent company.


Previous Post: Frustration

In the previous post, the concept of Frustration was defined and discussed with regard to the system of Experience.  In this post, the Lens of the System of Experience is used to reveal distinct categories of perceived Variation and the different ways the system responds to them.  Everyone should feel encouraged to join the discussion and comment on or debate the assertions presented. All relevant comments are welcome and appreciated.

Variation, Chance and Randomness

Discrepancies between Prediction and Perception can either be evaluated positively or negatively, in terms of the current efforts’ Efficiency tradeoff.  When these variations between Prediction and Perception are significant, the Variation itself becomes a subject of Attention effort for the Cognitive Model of the world.  The Variation will be modeled according to Perception, Memory and any relevant associations to other Cognitive Model subsets to arrive at a more reliable Prediction of that variance.  Motivation will focus one’s Attention on significant Variation to try and arrive at a state of Understanding regarding its nature.

There are three broad categories of Variation that will be considered by the system of Experience: Variation, Chance and Randomness.  True Variation is a discrepancy that follows a set of consistent rules one is able to discern.  Chance is discrepancy that is not predictable in nature, but is predictable in degree, range or scope.  Randomness is truly unpredictable; with no patterns or discernable structure and no bounds to the scope of the discrepancy.

If successive Perception is acquired, and significant Memory is built up regarding the nature of the Variation, a more accurate evaluation of the Variation is possible, based on the discrepancies between Prediction and Perception.  In light of the current tasks leading toward Understanding and their predicted Efficiency gains, discrepancies between the Prediction and Perception of Variation that impact the tasks are seen as either potential risks to the predicted value of the exchange of Attention and Efficiency or as potential opportunities to minimize the Attention cost or to increase Efficiency gain.  If the Variation is predictable in some way, there is a potential to exploit the Variation and achieve a more valuable Efficiency tradeoff than previously predicted.  In this situation, the Variation can be seen as relatively interesting and it will likely continue to be attended to.  However, if the Variation is evaluated as wholly unpredictable, as in Randomness, the Motivation evaluation highlights an increased risk to the predicted Efficiency tradeoff of the current associated effort toward Understanding.  Perceived Randomness is a significant threat to the goal of Understanding in general.

Next Post: Competency, Autonomy and Relatedness


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