John R. Koza's scientific contributions

Citations

... Neural Architecture Search (NAS) uses different approaches like EAs, reinforcement learning, and Bayesian optimization to find near-optimal architectures for Deep Neural Networks (DNNs) (Miikkulainen et al., 2019;Zoph et al., 2018;Lu et al., 2019). Genetic Programming (GP) and Grammatical Evolution (GE) (Ryan et al., 1998) enable solution generation and optimization simultaneously (Koza, 1994;Ryan et al., 1998;Miller, 2011), which makes them suitable candidates for simultaneous generation and training of neural networks (Tsoulos et al., 2008;Ahmadizar et al., 2015;Assunção et al., 2017a,b;Miller, 2020). In particular, GE (Ryan et al., 1998) is a variant of GP that takes a user-defined Context Free Grammar (CFG) as its input to determine how genotypes are mapped to phenotypes. ...