@inproceedings{1144154,
  added-at = {2008-06-19T17:46:40.000+0200},
  address = {Seattle, Washington, USA},
  author = {Walker, James Alfred and Miller, Julian Francis},
  biburl = {http://www.bibsonomy.org/bibtex/2dae12a51b2b2388fee40ac9e2c311b61/brazovayeye},
  booktitle = {{GECCO 2006:} Proceedings of the 8th annual conference
                 on Genetic and evolutionary computation},
  doi = {doi:10.1145/1143997.1144154},
  editor = {Keijzer, Maarten and Cattolico, Mike and Arnold, Dirk and Babovic, Vladan and Blum, Christian and Bosman, Peter and Butz, Martin V. and {Coello Coello}, Carlos and Dasgupta, Dipankar and Ficici, Sevan G. and Foster, James and Hernandez-Aguirre, Arturo and Hornby, Greg and Lipson, Hod and McMinn, Phil and Moore, Jason and Raidl, Guenther and Rothlauf, Franz and Ryan, Conor and Thierens, Dirk},
  interhash = {7ed90c1560381176f19dbcdee8f6df36},
  intrahash = {dae12a51b2b2388fee40ac9e2c311b61},
  isbn = {1-59593-186-4},
  keywords = {Cartesian acquisition, algorithms, automatically defined embedded evolution, functions, genetic hierarchical-if-and-only-if, lawnmower module problem, program programming, synthesis synthesis,},
  month = {8-12 July},
  notes = {GECCO-2006 A joint meeting of the fifteenth
                 international conference on genetic algorithms
                 (ICGA-2006) and the eleventh annual genetic programming
                 conference (GP-2006).

                 ACM Order Number 910060},
  organisation = {ACM SIGEVO (formerly ISGEC)},
  pages = {911--918},
  publisher = {ACM Press},
  publisher_address = {New York, NY, 10286-1405, USA},
  timestamp = {2008-06-19T17:46:40.000+0200},
  title = {Embedded cartesian genetic programming and the
                 lawnmower and hierarchical-if-and-only-if problems},
  url = {http://www.cs.bham.ac.uk/~wbl/biblio/gecco2006/docs/p911.pdf},
  volume = 1,
  year = 2006
}

@mastersthesis{Robinson:2001:GPtieus,
  abstract = {Part I: Background

                 1 INTRODUCTION

                 1.1 BACKGROUND ? AUTOMATIC PROGRAMMING

                 1.2 THIS PROJECT

                 1.3 SUMMARY OF CHAPTERS 2 GENETIC PROGRAMMING
                 REVIEW

                 Part II: PushGP

                 3 THE PUSH LANGUAGE & PUSHGP

                 4 PUSHGP COMPARED TO GP2 WITH ADFS

                 4.1 CAN A MORE FLEXIBLE SYSTEM PERFORM AS WELL?

                 4.2 THE COMPUTATIONAL EFFORT METRIC

                 4.3 MEASURING MODULARITY

                 4.4 SOLVING SYMBOLIC REGRESSION 4.5 EVEN PARITY AS A GP
                 BENCHMARK 4.6 SOLVING EVEN-FOUR-PARITY USING PUSHGP AND
                 STACK INPUT

                 4.7 EVEN-FOUR-PARITY WITH INPUT FUNCTIONS

                 4.8 EVEN-SIX-PARITY

                 4.9 SOLVING EVEN-N-PARITY

                 4.10 CONCLUSIONS DRAWN FROM THIS CHAPTER

                 5 VARIATIONS IN GENETIC OPERATORS

                 5.1 PERFORMANCE OF BASE PUSHGP OPERATORS

                 5.2 VARIATIONS IN CROSSOVER

                 5.3 VARIATIONS IN MUTATION

                 5.4 EMPIRICAL TESTS WITH NEW OPERATORS

                 5.5 CONCLUSIONS DRAWN FROM THESE RUNS

                 6 NEWGROUND ? EVOLVING FACTORIAL

                 Part III: LJGP

                 7 LINEAR CODED GENETIC PROGRAMMING IN JAVA

                 7.4 DISTRIBUTED PROCESSING

                 8 LJGP USER?S GUIDE

                 8.1 ENCODING A PROBLEM

                 8.2 LJGP PACKAGES AND CLASSES OVERVIEW

                 8.3 VCPU PROGRAMS

                 9 LJGP APPLIED

                 9.1 LAWNMOWER PILOT STUDY

                 9.2 PROBLEM DESCRIPTION

                 9.3 THE GENETIC MAKEUP OF AN INDIVIDUAL

                 9.4 THE MECHANICS OF EVOLUTION

                 9.5 PILOT RUNS OF THE LAWNMOWER PROBLEM

                 9.6 GRAZER PILOT STUDY

                 9.7 CONCLUSION TO LJGP APPLIED

                 Conclusion

                 APPENDIX A. COMPUTATIONAL EFFORT ? LISP CODE

                 APPENDIX B. GENETIC PROGRAMMING SYSTEMS IN
                 JAVA

                 APPENDIX C. LJGP/JAVA-VM BENCHMARKS},
  added-at = {2008-06-19T17:46:40.000+0200},
  author = {Robinson, Alan},
  biburl = {http://www.bibsonomy.org/bibtex/2ce98045ba4cda0b182f3da907a11c5e4/brazovayeye},
  interhash = {e95ef3c460079f574a1f2c08f4170e0d},
  intrahash = {ce98045ba4cda0b182f3da907a11c5e4},
  keywords = {GP, Grazer Java LJGP Lawnmower Linear PushGP, algorithms, genetic problem problem, programming,},
  month = May,
  school = {Hampshire College},
  size = {127 pages},
  timestamp = {2008-06-19T17:46:40.000+0200},
  title = {Genetic Programming: Theory, Implementation, and the
                 Evolution of Unconstrained Solutions},
  type = {Division III thesis},
  url = {http://citeseer.ist.psu.edu/498673.html},
  year = 2001
}