A framework for the design and evaluation of magic tricks that utilises computational systems configured with psychological constraints
Abstract
A human magician blends science, psychology and performance to create a magical e ect.
This thesis explores what can be achieved when that human intelligence is replaced or
assisted by machine intelligence. Magical e ects are all in some form based on hidden
mathematical, scienti c or psychological principles; the parameters controlling these
underpinning techniques are hard for a magician to blend to maximise the magical e ect
required. The complexity is often caused by interacting and con
icting physical and psychological
constraints that need to be optimally balanced. Normally this tuning is done
by trial and error, combined with human intuitions. This thesis focuses on applying Arti-
cial Intelligence methods to the creation, and optimisation, of magic tricks exploiting
mathematical principles. Experimentally derived, crowd sourced, data about particular
perceptual and cognitive features is used, combined with a model of the underlying
mathematical process, to provide a psychologically valid metric to allow optimisation of
magical impact. The thesis describes an optimisation framework that can be
exibly
applied to a range of di erent types of mathematics based tricks. Three case studies
are presented as exemplars of the methodology at work, the outputs of which are: language
and image based prediction and mind reading tricks, a magical jigsaw, and a
mind reading card trick e ect. Each trick created is evaluated through testing at public
engagement events, and in a laboratory environment. Further, a demonstration of the
real world e cacy of the approach for professional performers is presented in the form
of sales of the tricks in a reputable magic shop in London.
Authors
Williams, Howard ManningCollections
- Theses [3831]