Human Guidance Approaches for the Genetic Improvement of Software
Author:
Affiliation:
1. School of Computing and Communications, Lancaster University, Lancaster, United Kingdom
2. University of York, York, United Kingdom
Funder
Leverhulme Trust
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3643692.3648263
Reference13 articles.
1. Long Ouyang et al. 2022. Training language models to follow instructions with human feedback. arXiv:2203.02155 [cs.CL]
2. Ivo Gonçalves Sara Silva Joana B. Melo and Joao Carreiras. 2012. Random Sampling Technique for Overfitting Control in Genetic Programming. 218--229.
3. Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Making
4. Harsurinder Kaur, Husanbir Singh Pannu, and Avleen Kaur Malhi. 2019. A Systematic Review on Imbalanced Data Challenges in Machine Learning: Applications and Solutions. ACM Comput. Surv. 52, 4, Article 79 (aug 2019), 36 pages.
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