This file is about Algorithmic psychology.
In this file, I have summarised both the live lecture 9 as well as the according to literature. It entails all the information required for both the assignments as well as the exam.
, Lecture & Literature - Summary
Algorithmic psychology
An example: Theory of social space (not
necessary to learn)
When you model a too advance theory, you are not building an application!
When somebody likes someone else, it is based on:
Similarity
o Age,
o Race,
o Sex,
o Religion
Propinquity (closeness) of residence
o Whether they live in the neighborhood or not
Double arrow = related
Negative double arrow = negative relation
More far away, feels less similar
More similar, feels like less far away
Less dissimilar feels more near
Machine-learning mastery: kNN algorithm
K-nearest neighbors theory = a theory about the way humans befriend each other
The robot is looking for
a friend the way
humans do.
If the robot is only in
the care home, k=3
(since there are 3 other
people to possibly
befriend). Since there
are 2 old men and 1 old
woman, the robot will
try to befriend the 2
men because they form
the biggest group.
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