Genetic L-System Programming

By Christian Jacob. 1994

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Rafal Kicinger
2. Tomasz Arciszewski
3. J. Urgen Schmidhuber
4. Kenneth De Jong
5. David R Ha
6. Yoshua Bengio
7. Sergey Levine
8. Chelsea Finn

Citations in the corpus

• Deep learning in neural networks: An overview (2014, background): “, through Lindenmeyer Systems (Lindenmayer, 1968; Jacob et al., 1994), graph rewriting (Kitano, 1990), Cellular Encoding (Gruau et al.”
• On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models (2015, methodology): “However, the search space can often be reduced dramatically by evolving compact encodings of neural networks (NNs), e.g., through Lindenmeyer Systems [115], graph rewriting [127], Cellular Encoding [83], HyperNEAT [268], and other techniques [245, Sec.”
• Evolutionary computation and structural design: A survey of the state-of-the-art (2005, background): “The most popular examples of indirect representations are grammars [77], trees [78,79], shape grammars [80-83], graphs and matroids [84], cellular automata [85,86], Lsystems [55,87,88], and embryogenies [56].”