TY - GEN
T1 - Improving the effectiveness of genetic programming using continuous self-adaptation
AU - Griffiths, Thomas D.
AU - Ekárt, Anikó
PY - 2018/4/19
Y1 - 2018/4/19
N2 - Genetic Programming (GP) is a form of nature-inspired computing, introduced over 30 years ago, with notable success in problems such as symbolic regression. However, there remains a lot of relatively unexploited potential for solving hard, real-world problems. There is consensus in the GP community that the lack of effective real-world benchmark problems negatively impacts the quality of research [4]. When a GP system is initialised, a number of parameters must be provided. The optimal setup configuration is often not known, due to the fact that many of the values are problem and domain specific, meaning the GP system is unable to produce satisfactory results. We believe that the implementation of continuous self-adaptation, along with the introduction of tunable and suitably difficult benchmark problems, will allow for the creation of more robust GP systems that are resilient to failure.
AB - Genetic Programming (GP) is a form of nature-inspired computing, introduced over 30 years ago, with notable success in problems such as symbolic regression. However, there remains a lot of relatively unexploited potential for solving hard, real-world problems. There is consensus in the GP community that the lack of effective real-world benchmark problems negatively impacts the quality of research [4]. When a GP system is initialised, a number of parameters must be provided. The optimal setup configuration is often not known, due to the fact that many of the values are problem and domain specific, meaning the GP system is unable to produce satisfactory results. We believe that the implementation of continuous self-adaptation, along with the introduction of tunable and suitably difficult benchmark problems, will allow for the creation of more robust GP systems that are resilient to failure.
KW - Benchmarks
KW - Genetic programming
KW - Self-adaptation
KW - Tartarus
UR - http://www.scopus.com/inward/record.url?scp=85045978227&partnerID=8YFLogxK
UR - https://link.springer.com/chapter/10.1007%2F978-3-319-90418-4_8
U2 - 10.1007/978-3-319-90418-4_8
DO - 10.1007/978-3-319-90418-4_8
M3 - Conference publication
AN - SCOPUS:85045978227
SN - 9783319904177
VL - 732
T3 - Communications in Computer and Information Science
SP - 97
EP - 102
BT - Artificial Life and Intelligent Agents - Second International Symposium, ALIA 2016, Revised Selected Papers
PB - Springer
T2 - 2nd International Symposium on Artificial Life and Intelligent Agents, ALIA 2016
Y2 - 14 June 2016 through 15 June 2016
ER -