Computational Intelligence - February 2017 - 6

Simon M. Lucas
University of Essex,
Colchester, UK

IEEE CIS VP-Education Vision Statement

I

am very fortunate to be taking on
the role of vice president for education, especially when my predecessor Cesare Alippi has done such a great
job of setting up a well-organized
committee, and taken some very positive actions to promote the educational
activities of the IEEE Computational
Intelligence Society.
The role of the education committee
can be simply defined: to educate the
world about the value of computational
intelligence (CI) and the potential it has
to excel at the most challenging tasks,
and also to contribute fresh insight into
the very nature of intelligence.
During my time as vice president I
aim to build on the solid foundations of
the educational activities the IEEE has
enabled, by helping CI play a stronger
role in higher education. I also want to
make a concerted effort to push CI into
the areas that pose special challenges:
pre-university education and continuing education.
Promoting CI in pre-university education is a challenge, because several of
the methods we study and employ in
the type of CI used by the IEEE and in
higher education, do not usually appear
in secondary school curricula, or at least
in the way that we would like them to.
For example, while secondary school
students learn about evolution from a
biological perspective within their biology classes, they do not normally study
it in computer science or mathematics
classes. This is a shame, because as we
know, evolutionary algorithms at their
heart are so wonderfully simple and
powerful, that they could significantly
enhance computer science education in
schools. Given the tight controls on curricula, this is unlikely to happen formally any time soon, but may be

Digital Object Identifier 10.1109/MCI.2016.2627665
Date of publication: 6 January 2017

6

encouraged behind the scenes with promotion of the use of CI for group or
individual project work, where topics
are normally less constrained.
Securing greater CI awareness in
continuing education is a different type
of challenge: industry has already fallen
in deeply love with the idea of deep
learning systems, but the love can often
remain unrequited, with a shortage of
deep learning talent available for hire.
This is an area for which we can help to
provide resources or pointers to existing
material, in order to help industry practitioners stay up to the minute, and the
IEEE CIS Education website already
provides a set of useful services to support this in the form of course material
and videos.
There has never been a better time
for computational intelligence. The
essence of CI lies in the way that intelligence can emerge or evolve naturally
from the statistics and interactions of
simple computational elements and paradigms. The last decade has seen a stepchange in our knowledge of how to do
this, and in the availability of the computing power needed to achieve awesome results.
While not strictly the remit of the
education committee, an issue the CIS
needs to address is how to gain more
publicity for what we do and promote.
For example, there exist some valuable
resources in our education vault, but
many of the videos only have a modest
number of views, despite offering highquality recordings of leading international keynote addresses. We somehow
need better ways to channel viewers to
the existing resources, and smart use of
social media is an area where CIS has
some catching up to do, and the education committee will play its part.
Although the remit of the education
committee is broad, the single most
important area I'd like to grow during

IEEE ComputatIonal IntEllIgEnCE magazInE | FEbruary 2017

my term as vice president is the competitions we run, and it is this aspect
that I will focus on for the remainder
of this article.
There are many types of artificial
intelligence (AI) competition and they
vary greatly in many ways, including
their: complexity to enter, level of participation, scientific interest, public
engagement, "levelness of playing field,"
evaluation criteria, and timelines (continuously running evaluation versus
event-based). Some organizations such
as DARPA have fully embraced the idea
of competitions, with the famous
DARPA Grand Challenge for autonomous vehicles (https://en.wikipedia.
org/wiki/DARPA_Grand_Challenge),
which provided a great impetus for
research in self-driving cars and high
levels of public engagement, although
requiring a high cost to run and asking a
large fee of entrants.
Within the IEEE CIS our competitions have been run with more modest
budgets, often comprising the time and
effort of university staff and students to
organise and run the competitions. The
process often involved writing bespoke
software to evaluate the entries. Competitions have been run in association with
our three main conferences: FUZZIEEE, CEC and IJCNN, with the latter
two coordinating the majority. Examples
of regular competitions running in conjunction with these conferences include
many different types of optimization
(CEC), time series prediction (IJCNN)
and causal analysis (IJCNN). However,
the conference series with the strongest
record of competition development has
been IEEE CIG - which this year had
eight competitions associated with it,
including General Video Game AI
(http://gvgai.net) and VizDoom
(http://vizdoom.cs.put.edu.pl/).
Games stand out as an especially
interesting way to engage both research
https://www.en.wikipedia http://www.gvgai.net http://vizdoom.cs.put.edu.pl/
Table of Contents for the Digital Edition of Computational Intelligence - February 2017
