We presents a general problem-solving method combining
the principles of artificial intelligence and
evolutionary computation. The problem-solving method is
based on the computer language GENETICA, which stands
for Genetic Evolution of Novel Entities Through the
Interpretation of Composite Abstractions. GENETICAs
programming environment includes a computational system
that evolves data abstractions, viewed as genotypes of
data generation scenarios for a GENETICA program, with
respect to either confirmation or optimisation goals. A
problem can be formulated as a GENETICA program, while
the solution is represented as a data structure
resulting from an evolved data generation scenario.
This approach to problem solving offers: 1) generality,
since it concerns virtually any problem stated in
formal logic; 2) effectiveness, since formally
expressed problem-solving knowledge can be incorporated
in the problem statement; and 3) creativity, since
unpredictable solutions can be obtained by evolved data
structures. It is shown that domain specific languages,
including genetic programming ones, that inherit
GENETICAs features can be developed in GENETICA. The
language G-CAD, specialised to problem solving in the
domain of architectural design, is presented as a case
study followed by experimental results.
%0 Journal Article
%1 virirakis:2003:TEC
%A Virirakis, Lefteris
%D 2003
%J IEEE Transactions on Evolutionary Computation
%K CAD, G-CAD, GENETICA, GP, abstractions, algorithms, architectural artificial computation, computer data design, domain environment environments, evolutionary evolving experimental expression, formal general generation genetic genotypes, high intelligence, language, languages, level logic, method, optimization, problem problem-solving problem-solving, programming programming, results, scenarios, solving, specific structure, structures,
%N 5
%P 456--481
%R doi:10.1109/TEVC.2003.816581
%T GENETICA: A Computer Language That Supports
General Formal Expression With Evolving Data
Structures
%V 7
%X We presents a general problem-solving method combining
the principles of artificial intelligence and
evolutionary computation. The problem-solving method is
based on the computer language GENETICA, which stands
for Genetic Evolution of Novel Entities Through the
Interpretation of Composite Abstractions. GENETICAs
programming environment includes a computational system
that evolves data abstractions, viewed as genotypes of
data generation scenarios for a GENETICA program, with
respect to either confirmation or optimisation goals. A
problem can be formulated as a GENETICA program, while
the solution is represented as a data structure
resulting from an evolved data generation scenario.
This approach to problem solving offers: 1) generality,
since it concerns virtually any problem stated in
formal logic; 2) effectiveness, since formally
expressed problem-solving knowledge can be incorporated
in the problem statement; and 3) creativity, since
unpredictable solutions can be obtained by evolved data
structures. It is shown that domain specific languages,
including genetic programming ones, that inherit
GENETICAs features can be developed in GENETICA. The
language G-CAD, specialised to problem solving in the
domain of architectural design, is presented as a case
study followed by experimental results.
@article{virirakis:2003:TEC,
abstract = {We presents a general problem-solving method combining
the principles of artificial intelligence and
evolutionary computation. The problem-solving method is
based on the computer language GENETICA, which stands
for Genetic Evolution of Novel Entities Through the
Interpretation of Composite Abstractions. GENETICAs
programming environment includes a computational system
that evolves data abstractions, viewed as genotypes of
data generation scenarios for a GENETICA program, with
respect to either confirmation or optimisation goals. A
problem can be formulated as a GENETICA program, while
the solution is represented as a data structure
resulting from an evolved data generation scenario.
This approach to problem solving offers: 1) generality,
since it concerns virtually any problem stated in
formal logic; 2) effectiveness, since formally
expressed problem-solving knowledge can be incorporated
in the problem statement; and 3) creativity, since
unpredictable solutions can be obtained by evolved data
structures. It is shown that domain specific languages,
including genetic programming ones, that inherit
GENETICAs features can be developed in GENETICA. The
language G-CAD, specialised to problem solving in the
domain of architectural design, is presented as a case
study followed by experimental results.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Virirakis, Lefteris},
biburl = {https://www.bibsonomy.org/bibtex/2b84c380cd71e0eb95c9d9e0ecbe8b1b2/brazovayeye},
doi = {doi:10.1109/TEVC.2003.816581},
interhash = {5a2cc0a6dcd5bc7426afec22cf13542d},
intrahash = {b84c380cd71e0eb95c9d9e0ecbe8b1b2},
issn = {1089-778X},
journal = {IEEE Transactions on Evolutionary Computation},
keywords = {CAD, G-CAD, GENETICA, GP, abstractions, algorithms, architectural artificial computation, computer data design, domain environment environments, evolutionary evolving experimental expression, formal general generation genetic genotypes, high intelligence, language, languages, level logic, method, optimization, problem problem-solving problem-solving, programming programming, results, scenarios, solving, specific structure, structures,},
month = {October},
notes = {Inspec Accession Number: 7757988},
number = 5,
pages = {456--481},
size = {26 pages},
timestamp = {2008-06-19T17:53:40.000+0200},
title = {{GENETICA}: {A} Computer Language That Supports
General Formal Expression With Evolving Data
Structures},
volume = 7,
year = 2003
}