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BASIC TOPICS IN EXPERIMENTAL
1997 Jun 24, 5:46 p.m.
Computer science has an experimental scientiﬁc aspect—like every
other science. Experiments are made with suitable computer programs
in order to discover facts. The programs are usually not applications
but specialized to the scientiﬁc problem being investigated.
It is a
mistake to divide computer science simply into theoretical and applied
parts. Basic computer science has both theoretical and applied parts.
Applied computer science certainly has an experimental part, and
presumably it has a theoretical part also.
We wouldn’t expect to have to tell you this.
Unfortunately, many computer scientists and other people divide
computer science into theoretical and applied computer science, leav-
ing no place for basic experimental work.
This report describes basic experimental work in several domains
of computer science.
Some computer scientists and some computer engineers mistakenly identify
basic research with theory and applied research with experiment. A recent
report by the National Research Council Academic Careers for Experi-
mental Computer Scientists and Engineers1 [Cou95] was particularly
bad about this. All the experimental work mentioned was explicitly applied,
i.e. in support of speciﬁc applied projects. This may have something to do
with the persistent tendency of that body to deny any distinction between
science and engineering in computing.
However, computer science also has an important basic research experi-
mental component, and our object is to describe some of this work enough to
show the important role experiment plays in basic computer science research.
At present this is only an outline.
Here are some topics:
search Richard Korf (email@example.com) will write a section on this.
game playing Turing proposed a chess program in the 1940s, and recently
Deep Blue had a match with the world champion. The experimental
chess programs have taught a lot about heuristics and what computa-
tional abilities are required to match human performance. The failure
to make good Go programs illustrates that we still don’t understand
how to make a program that breaks a situation up into components
that can be analyzed separately at ﬁrst, following this by an analysis
of their interaction. Jonathan Schaeﬀer of the University of Alberta,
(firstname.lastname@example.org) has written about the role of experiment in
game playing. There are html2 and postscript3 versions.
automatic theorem proving Again the experimental work has shown us
the strengths and weaknesses of various theoretical ideas. Alan Bundy
(email@example.com) has already ﬁnished a draft.
It is Experi-
mental Work in ATP4.
planning Most of the research in planning under uncertainty has a strong
experimental component. Subbarao Kambhampati (firstname.lastname@example.org) has
agreed to write about this.
experiments with NP-complete problems Problems that are NP-completein general are often much easier in the average case. This has been ex-
plored experimentally, and a phase change phenomenon between cases
with many solutions and cases with no solutions has turned up. This
seems to be analogous to phase changes in physics.
Bart Selman (email@example.com) will write about experimental
study of NP-completeness in AI including phase transitions, search and
Andrew Goldberg (firstname.lastname@example.org) has written about exper-
imental algorithms. We have html5 and .ps6 versions.
Actually Goldberg and Selman will divide up their topics in a way they
will shortly specify more precisely.
natural language Fernando Pereira (PEREIRA@RESEARCH.ATT.COM)
will write about experimental research in natural language.
vision Tom Binford (email@example.com) will write about vision.
neural nets Jordan Pollack (firstname.lastname@example.org) will write about neu-
ral nets and evolutionary programming.
connectionism Geoﬀrey Hinton (email@example.com) will write about
connectionism. Hinton dropped out for lack of time, so we need some-
one to write about connectionism.
machine learning Tom Dietterich, TGD@CS.ORST.EDU has written aboutexperimental research in machine learning. We have .html7 and gzipped
[Cou95] National Research Council. Academic careers for experimental com-
puter scientists and engineers, 1995.
/@steam.stanford.edu:/u/ftp/jmc/experimental.tex: begun 1996 May 23, latexed 1997 Jun 24 at 5:46 p.m.