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Simplicity TheorySimplicity TheorySimplicity TheorySimplicity Theory

InterestEmotional

intensity

InterestEmotional intensity

Simplicity theoryis a cognitive theory

Simplicity is known to play a role in cognition.For instance, the brain reconstructs hidden shapes

by computing the simplest contours in the current context.Simplicity controls

high-level aspects of cognition as well.

Situations that are perceived as abnormally simple

are exactly those that raise our interest

and arouse our emotions.

J.-L. Dessalles



Complexity:

Size of the minimal available description

Simplicity Theory:

Complexity drop

blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah

16 blah

Simplicity theoryrelies on the notion of

complexity.

Complexity has been defined half a century agoas the size of the most concise description.

Simplicity theory is not about complexity,

but complexity drop



U = Cexp – Cobs

Expectedcomplexity

Observedcomplexity

InterestEmotional

intensity


Complexity drop

Unexpectedness

ST defines Unexpectedness as the

difference between expected complexity and

observed complexity.

Unexpectednessis what controls

interest andemotional intensity.



U = Cexp – Cobs

Expectedcomplexity

Observedcomplexity

Complexity drop

Unexpectedness

12 17 24 32 39 40 1 2 3 4 5 6 Lottery draw:

For instance, a lottery draw

is expected to be complex.

If it turns out to be simple, for instance 1-2-3-4-5-6,

interest is aroused.



U = Cexp – Cobs

Coincidences

Recency

Proximity

Rarity

Extremes

Anomalies


Interest

Emotional intensity

Abnormal

simplicity

Interest, emotions andunexpectedness seem to

depend on a variety of factors.

However,all these factors

turn out to generatecomplexity drop.



U = Cexp – Cobs

Coincidences

Recency

Proximity

Rarity

Extremes

Anomalies

Complex, analogous events

Logarithmic decrease with time

Simple feature

Logarithmic decrease with distance

Simple feature

Simple feature

predictions

Abnormal

simplicity

ST’s analysis of unexpectedness as

complexity dropleads to a variety of

predictions.



U = Cexp – Cobs

Coincidences

Recency

Proximity

Rarity

Extremes

Anomalies

U = C(s1) C (s2|s1)

U = 2 log(R / d)L = argmin(C(L) + 2log(dL))

U = log(T / t)

U = log N – log P – C(f)

U = A(k) – C(f)

U = C(H) – C(f)

predictions

Abnormal

simplicity

These predictions are formal and

quantitative.



U = Cexp – Cobs

Simplicity Theory’s most spectacular

result is a new definition of ex post

probability.

p = 2 –U



U = Cexp – Cobs

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