Links and References
The main fields of research within the framework of evolutionary computation, related to the GENETICA approach, are the fields of genetic algorithms (GA) and genetic programming (GP). Some ideas and techniques within the GENETICA approach originated from either GA or GP methods dealing with formal logic.
The G-CAD approach to architectural designing, presented in this site, combines features of Artificial Intelligence (AI) and evolutionary approaches to architectural designing. Some ideas and techniques within the G-CAD approach originated from the design method CADRAM.
The evolutionary approach to design, as well as other approaches based on biological paradigms, could be combined in the framework of integrated building.
Both web-sites and references to the aforementioned fields of research are given here.
Web-sites
Introduction: http://www.boente.eti.br/fuzzy/ebook-fuzzy-mitchell.pdf
Sources of information: http://geneticalgorithms.ai-depot.com/
http://www.talkorigins.org/faqs/genalg/genalg.html
Textbooks
[1] J.H. Holland, Adaptation in Natural and Artificial
Systems: An Introductory Analysis with Applications to Biology, Control and
Artificial Intelligence.
[2] D.E. Goldberg, Genetic Algorithms in Search, Optimization
and Machine Learning.
[3] M. Mitchell, An
Introduction to Genetic Algorithms.
Web-sites
Introduction: http://www.genetic-programming.com/gpanimatedtutorial.html
Main web-sites: http://www.genetic-programming.org/
http://www.genetic-programming.com/
Textbooks
[1] J.R. Koza, Genetic Programming: On the Programming of
Computers by Means of Natural Selection.
[2] J.R. Koza, Genetic Programming II: Automatic Discovery
of Reusable Programs.
[3] J.R.
Koza, F.H. Bennett, D. Andre, and M.A. Keane, Genetic Programming III Darwinian Invention and
Problem Solving.
[4] W.B. Langdon, Genetic Programming and data structures:
Genetic Programming + data structures = automatic programming.
[5] W. B. Langdon and R. Poli, Foundations of Genetic Programming. Springer, 2002 (ISBN 3-540-42451-2)
[6] W.
Banzhaf, P. Nordin, R.E. Keller, and F.D. Francone, Genetic Programming—An Introduction.
Evolutionary
Methods Related to Formal Logic
References
[1] C. Chakraborti and K.K.N. Sastry, “The Genetic Algorithms approach for proving logical arguments in natural language,” in Proceedings of the Third Annual Genetic Programming Conference, J.R. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D.B. Fogel, M.H. Garzon, D.E. Goldberg, H. Iba, R.L. Riolo, Eds. San Francisco, California: Morgan Kaufmann Publishers, 1998, pp. 463-470.
[2] F. Divina, and E. Marchiori,
“Knowledge based evolutionary programming for inductive learning in first-order
logic,” in GECCO-2001 Proceedings of the Genetic and Evolutionary
Computation Conference, L. Spector, E.D. Goodman, A. Wu,
W.B. Langdon, H-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk,
M.H. Garzon, E. Burke Eds.
[3] Matthias Fuchs, “Evolving
term features: first steps,” Automated reasoning project, Research School of
Information Sciences and Engineering,
Available:
http://arp.anu.edu.au:80/ftp/techreports/1999/TR-ARP-04-99.ps.gz
[4] Marc
Fuchs, Dirk Fuchs, Matthias Fuchs, “Generating lemmas
for Tableau-based proof search using Genetic Programming,” in GECCO-99 Proceedings of the Genetic and Evolutionary Computation Conference,
W. Banzhaf, J. Daida, A.E. Eiben, M.H. Garzon,
V. Honavar, M. Jakiela, R.E. Smith, Eds. San Francisco,
California: Morgan Kaufmann Publishers, 1999, pp. 1027-1032.
[5] M. Keizer, V. Babovic, C. Ryan, M. O’Neill, and M. Catolico, “Adaptive Logic Programming,” in L. Spector at al. [2], pp. 42‑49.
[6] I. Muslea, “A general-purpose AI Planning system based on the Genetic Programming paradigm,” in Late Breaking Papers at the Genetic Programming 1997 Conference, J.R. Koza, Ed. CA, USA: Stanford University, 1997, pp. 157-164.
[7] K. Musumbu, K. Barbar, and M. Nassif, “Evolution Strategies to improve abstract interpretation algorithms for Logic Programming,” in J.R. Koza, Ed. [6], pp. 165-173.
[8] P.G.K. Reiser, and P.J.
Riddle, “Evolving logic programs to classify chess-endgame positions,” in Simulated Evolution and Learning: selected
papers / Second
[9] B.J. Ross, “Logic-based Genetic Programming with Definite Clause
Translation Grammars,” in
[10] A. Tamaddoni-Nezhad, and
Architectural
Design Problem Solving Theories and Methods
[1] R.D. Coyne and J.S. Gero, “Logic programming as a means of representing semantics in design languages,” Environment and Planning B: Planning and Design, vol. 12, pp. 351-369, 1985.
[2] R.D. Coyne and J.S. Gero, “Design knowledge and context,” Environment and Planning B: Planning and Design, vol. 12, pp. 419-442, 1985.
[3] C.M. Eastman, “Logical Methods of building design : a synthesis and review,” DMG-DRS Journal: Design research and methods, vol. 6 (3), pp. 79-87, 1972.
[4] C. Kyriazopoulos, “The CADRAM program: an application for CAAD based on the primitives’ Allocation Method,” Diploma Thesis, Department of Architectural Engineering, National Technical University of Athens, 1995 (available from the Library of Department of Architectural Engineering and from the author).
[5] W.J. Mitchell, “The theoretical foundation of computer-aided architectural design,” Environment and Planning B: Planning and Design, vol. 2, pp. 127-150, 1975.
[6] P.S.G. Swinson, “PROLOG: a prelude to a new generation of CAAD,” Environment and Planning B: Planning and Design, vol. 15, pp. 335-343, 1983.
[1] A.G. De Silva Garza and M.L. Maher, “A process model for evolutionary design case adaptation,” in Artificial Intelligence in Design 00, J.S. Gero, Ed. Dordrecht: Kluwer Academic Publishers, 2000, pp. 393-412.
[2] J.S. Gero, and V. Kazakov, “Adapting evolutionary computing for
exploration in creative designing,” in Computational
Models of Creative Designing, J.S. Gero, M.L. Maher Eds. Sydney, Australia: Key Centre of
Design Computing and Cognition, University of
[3] J.S. Gero, “Novel models in evolutionary
designing,” in Simulated Evolution and
Learning: selected papers / Second
[4] J.S. Gero, and X-G. Shi, “Design development based on an analogy with developmental biology,” in CAADRIA’99, J. Gu, and Z. Wei, Eds. Shanghai, China: Shanghai Scientific and Technological Literature Publishing House, 1999, pp. 253-264.
[5] R. Jagielski, and J.S. Gero, “A genetic programming approach to the
space layout planning problem,” in CAAD
Futures 1997, R. Junge Ed. Kluwer, Dordrecht, 1997, pp. 875‑884.
[6] H. Lipson, and N.P. Suh, “Towards a
universal design-component architecture for design automation,” in Proceedings of ICAD2000 First
International Conference on Axiomatic Design. Cambridge, MA – June 21-23, 2000.
[7] M.A. Rosenman, and J.S. Gero, “Evolving
designs by generating useful complex gene structures,” in Evolutionary Design by Computers, P. Bentley, Ed. London: Morgan Kaufmann, 1999,
pp. 345-364.
[8] L. Virirakis, “The continuous search space design method (CSSDM),” Environment and Planning B: Planning and Design, vol. 20, pp. 617-643, 1993.
