NEAIDec 5, 2023

Liquid State Genetic Programming

arXiv:2312.14942v13 citationsh-index: 19ICANNGA
Originality Synthesis-oriented
AI Analysis

This is an incremental improvement for researchers in evolutionary computation, offering a new variant for benchmarking tasks.

The authors tackled the problem of improving Genetic Programming by proposing Liquid State Genetic Programming (LSGP), a hybrid method that combines dynamic memory with standard techniques, and found it performs similarly or better on benchmark problems.

A new Genetic Programming variant called Liquid State Genetic Programming (LSGP) is proposed in this paper. LSGP is a hybrid method combining a dynamic memory for storing the inputs (the liquid) and a Genetic Programming technique used for the problem solving part. Several numerical experiments with LSGP are performed by using several benchmarking problems. Numerical experiments show that LSGP performs similarly and sometimes even better than standard Genetic Programming for the considered test problems.

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