2022/11/30 by Max Vistrup, Vistrup, Max
Biochemistry, Genetics and Molecular Biology · Computer Science · #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE) #Reinforcement Learning in Robotics #Viral Infectious Diseases and Gene Expression in Insects
paper · pdf · doi:10.48550/arxiv.2211.17234
openalex publication_date 2022/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present new techniques for synthesizing programs through sequences of mutations. Among these are (1) a method of local scoring assigning a score to each expression in a program, allowing us to more precisely identify buggy code, (2) suppose-expressions which act as an intermediate step to evolving if-conditionals, and (3) cyclic evolution in which we evolve programs through phases of expansion and reduction. To demonstrate their merits, we provide a basic proof-of-concept implementation which we show evolves correct code for several functions manipulating integers and lists, including some that are intractable by means of existing Genetic Programming techniques.