Abstract Template

s 2008 "Population
Based
Incremental
Schema
Learning" Matt
Dominski
(Computer
Science) Advised
by
Dale
Brown
(CS)
 Abstract Evolutionary
algorithms
are
used
a
lot
to
solve
non‐polynomial
problems.
This
works
especially
well
 since
it
has
already
been
shown
that
they
are
able
to
Gind
near‐optimal
solutions.
This
project
will
focus
 on
the
genetic
algorithm
(GA)
and
the
population
based
incremental
learning
algorithm
(PBIL).
This
 paper
will
then
take
the
PBIL
and
add
functionality
to
the
PBIL
to
create
the
population
based
 incremental
schema
learning
(PBISL)
algorithm
which
uses
the
notion
of
schemata
from
the
GA.
The
 objective
of
this
paper
is
to
create
a
PBISL
and
compare
it
against
a
PBIL
and
a
genetic
algorithm.
This
 comparison
will
be
done
by
comparing
the
results
of
different
problems
like
the
parity,
0/1
knapsack
and
 the
traveling
salesman
problem. ****************************************************************************************** "Mobile
Robotics:
The
study
of
the
Mindstorms
Lego
NXT
Robotics
Kit
and
its
Applications
 in
Autonomous
Robotics" Richard
Lawrence
(Computer
Science) Advised
by
Denise
Byrnes
(CS)