Data crawlers for simple optical character recognition

Proceedings of the 2000 Congress on Evolutionary Computation, CEC 2000

Volumn 1, Issue , 2000, Pages 706-713

  Ashlock, Dan ^a  

^a IOWA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATA THEORY; CHARACTER SETS; EXPERT SYSTEMS; GENETIC ALGORITHMS; GENETIC PROGRAMMING; OPTICAL CHARACTER RECOGNITION; DECISION THEORY; FINITE AUTOMATA; ITERATIVE METHODS;

ADDITIONAL DATUM; DIGITAL EVOLUTION; EXTRACT INFORMATIONS; FINITE STATE; GENETIC PROGRAMMING SYSTEM; GENETIC PROGRAMMING TECHNIQUE; HIGH BANDWIDTH; STATE INFORMATION;

DIGITAL STORAGE; OPTICAL CHARACTER RECOGNITION;

DATA CRAWLERS; FINITE STATE MACHINES; GENETIC PROGRAMMING;

EID: 0033672289     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2000.870367     Document Type: Conference Paper

References (23)

1. [Andre, 1994] Andre, D. (1994). Automatically defined features: the simultaneous evolution of 2-dimensional feature detectors and an algorithm for using them. In Kinnear, K., editor, Advances in Genetic Programming, chapter 23. The MIT Press.
2. [Angeline, 1997a] Angeline, P. J. (1997a). An alternative to indexed memory for evolving programs with explicit state representations. In Genetic Programming 97., pages 423430, San Francisco. Morgan Kaufmann.
3. [Angeline, 1997b] Angeline, P. J. (1997b). Subtree crossover: Building block engine or macromutation? In Genetic Programming 97., pages 9-17, San Francisco. Morgan Kaufmann.
4. [Angeline, 1998] Angeline, P. J. (1998). Subtree crossover causes bloat. In Genetic Programming 98., pages 745-752, San Francisco. Morgan Kaufmann.
5. [Ashlock, 1997] Ashlock, D. (1997). Gp-automata for dividing the dollar. In GP 97, pages 18-26. MIT Press.
6. [Ashlock and Richter, 1997] Ashlock, D. and Richter, C. (1997). The effect of splitting populations on bidding strategies. In GP 97, pages 27-34. MIT Press.
7. [Ashlock et al., 1995] Ashlock, D., Smucker, M. D., Stanley, E. A., and Tesfatsion, L. (1995). An evolutionary iterated prisoner's dilemma game with choice and refusal of partners. To Appear in Biosystems.
8. [Ashlock and Oliver, 1996] Ashlock, J. W. D. and Oliver, J. (1996). Evolution of ultrasimple virtual robots. In Proceedings of the 1996 IEEE International Joint Symposia on Intelligence and Systems, pages 170-177. IEEE.
9. [Brave, 1996] Brave, S. (1996). Evolving deterministic finite state automata using cellular encoding. In Genetic Programming 96., pages 39-44, Cambridge, MA. MIT Press.
10. [Chellapilla, 1997] Chellapilla, K. (1997). Evolutionary programming without tree mutations: Evolving computer Programms without crossover. In Genetic Programming 97., pages 431-438, San Francisco. Morgan Kaufmann.
11. [Fogel, 1993] Fogel, D. (1993). Evolving behaviors in the iterated prisoners dilemma. Evolutionary Computation, 1(1).
12. [Fogel et al., 1965] Fogel, L., Owens, A., and Walsh, M. (1965). Artificial intellegence through a simulation of evolution. In Biophysics and Cybernetic Systems: Proceedings of the 2nd Cybernetic Sciences Symposium, pages 131-155, Washington D.C. Spartan Books.
13. [Gathercole and Ross, 1996] Gathercole, C. and Ross, P. (1996). An adverse interaction between crossover and restricted tree depth in genetic programming. In Genetic Programming 96., pages 291-296, San Francisco. Morgan Kaufmann.
14. [Goldberg, 1989] Goldberg, D. E. (1989). Genetic Algorithms in Search. Optimization, and Machine Learning. Addison-Wesley Publishing Company, Inc., Reading, MA.
15. [Harries and Smith, 1997] Harries, K. and Smith, P. (1997). Exploring alternative operators and search strategies in genetic programming. In Genetic Programming 97., pages 147-155, San Francisco. Morgan Kaufmann.
16. [Koza, 1992] Koza, J. R.. (1992). Genetic Programming. The MIT Press, Cambridge, MA.
17. [Koza, 1994] Koza, J. R. (1994). Automatic discovery of detectors for letter recognition. In Koza, J., editor, Genetic Programming II, chapter 15. The MIT Press, Cambridge, MA.
18. [Luke and Spector, 1997] Luke, S. and Spector, L. (1997). A comparison of crossover and mutation in genetic programming. In Genetic Programming 97., pages 240-248, San Francisco. Morgan Kaufmann.
19. [Miller, 1989] Miller, J. H. (1989). The coevolution of automata in the repeated prisoner's dilemma. A Working Paper from the SFI Economics Research Program 89-003, Santa Fe Institute and Carnegie-Mellon University, Santa Fe, NM.
20. [Richter et al., 1998] Richter, C, Ashlock, D., and Sheble, G. (1998). Effects of tree size and state number on gp-automata bidding strategies. In GP 98, pages 329-337. MIT Press.
21. [Siegel and Chaffee, 1996] Siegel, E. V. and Chaffee, A. D. (1996). Genetically optimizing the speed of programs evolved to play tetris. In Angeline, P. and Kinnear, K., editors, Advances in Genetic Programming. Volume 2, chapter 13. The MIT Press.
22. [Stanley et al., 1994] Stanley, E. A., Ashlock, D., and Tes-fatsion, L. (1994). Iterated prisoner's dilemma with choice and refusal. In Langton, C, editor, Artificial Life HI, pages 131-176, Reading. Addison-Wesley.
23. [Teller, 1994] Teller, A. (1994). The evolution of mental models. In Kinnear, K., editor, Advances in Genetic Programming, chapter 9. The MIT Press.