abstract = "Boolean function synthesis problems have served as
some of the most well studied bench-marks within
Genetic Programming (GP). Recently, these problems have
been addressed using Semantic Backpropagation (SB)
which was introduced in GP so as to take into account
the semantics (outputs over all fitness cases) of a GP
tree at all intermediate states of the program
execution, i.e. at each node of the tree. The mappings
chosen for reversing the operators used within a GP
tree are crucially important to SB. This thesis
describes the work done in designing and testing three
novel SB algorithms for solving Boolean and Finite
Algebra function synthesis problems. These algorithms
generally perform significantly better than other well
known algorithms on run times and solution sizes.
Furthermore, the third algorithms is deterministic, a
property which makes it unique within the domain.",
notes = "M2 Project part of Center for Complexity Science
Erasmus Mundus Masters in Complex Systems
https://www2.warwick.ac.uk/fac/cross_fac/complexity/study/emmcs/outcomes/studentprojects/
This work was conducted during a 6 month internship at
TAO team, INRIA, Saclay, France