Behavioral Program Synthesis:Insights and Prospects 183
Liskowski P, Krawiec K, Helmuth T, Spector L (2015) Comparison of semantic-aware selection
methods in genetic programming. In: Proceedings of the seventeenth annual conference on
genetic and evolutionary computation companion, GECCO Comp (accepted)
Lungarella M, Metta G, Pfeifer R, Sandini G (2003) Developmental robotics: a survey. Conn Sci
15:151–190
McKay RIB (2000) Fitness sharing in genetic programming. In: Whitley D, Goldberg D, Cantu-
Paz E, Spector L, Parmee I, Beyer HG (eds) Proceedings of the genetic and evolutionary
computation conference (GECCO-2000). Morgan Kaufmann, Las Vegas, pp 435–442.http://
http://www.cs.bham.ac.uk/~wbl/biblio/gecco2000/GP256.pdf
Miller GA (1983) Informavores. Wiley, New York, pp 111–113
Moraglio A, Krawiec K, Johnson CG (2012) Geometric semantic genetic programming. In: Coello
CA, Cutello V, Deb K, Forrest S, Nicosia G, Pavone M (eds) Parallel problem solving from
nature, PPSN XII (part 1). Lecture notes in computer science, vol 7491. Springer, Taormina,
pp 21–31. doi:10.1007/978-3-642-32937-1_3
Popovici E, Bucci A, Wiegand RP, de Jong ED (2011) Coevolutionary principles. In: Handbook of
natural computing. Springer, Heidelberg
Quinlan J (1992) C4.5: programs for machine learning. Morgan Kaufmann, San Mateo
Smith R, Forrest S, Perelson A (1993) Searching for diverse, cooperative populations with genetic
algorithms. Evol. Comput. 1(2):127–149
Sparkes A, Aubrey W, Byrne E, Clare A, Khan M, Liakata M, Markham M, Rowland J, Soldatova
L, Whelan K, Young M, King R (2010) Towards robot scientists for autonomous scientific
discovery. Autom Exp 2(1):1. doi:10.1186/1759-4499-2-1.http://www.aejournal.net/content/
2/1/1
Spector L, Robinson A (2002) Genetic programming and autoconstructive evolution
with the push programming language. Genet Program Evolvable Mach 3(1):7–40.
doi:10.1023/A:1014538503543.http://hampshire.edu/lspector/pubs/push-gpem-final.pdf
Swan J, Woodward J, Özcan E, Kendall G, Burke E (2014) Searching the hyper-heuristic design
space. Cogn Comput 6(1):66–73. doi:10.1007/s12559-013-9201-8
Tomassini M, Vanneschi L, Collard P, Clergue M (2005) A study of fitness distance cor-
relation as a difficulty measure in genetic programming. Evol Comput 13(2):213–239.
doi:10.1162/1063656054088549
Watson RA (2006) Compositional evolution: the impact of sex, symbiosis and modularity on the
gradualist framework of evolution. Vienna series in theoretical biology, vol NA. MIT Press,
Cambridge.http://eprints.ecs.soton.ac.uk/10415/