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![]() Title:Benchmarking Individual Representation in Grammar-Guided Genetic Programming Conference:Evo*2022 Tags:Derivation Trees, Grammar-Guided GP and Grammatical Evolution Abstract: Grammar-Guided Genetic Programming (GGGP) has two main flavors, Context-Free Grammar GP (CFG-GP) and Grammatical Evolution (GE). GE enjoys multiple benefits, leading to being the most widely-used approach. However, GE also suffers from disadvantages. In this paper, we first review the established advantages and disadvantages of both GE and CFG-GP. Then, we identify three new advantages of CFG-GP over GE: direct evaluation, in-node storage, and deduplication. We conclude that there is further need for studying the performance of CFG-GP and GE. Benchmarking Individual Representation in Grammar-Guided Genetic Programming ![]() Benchmarking Individual Representation in Grammar-Guided Genetic Programming | ||||
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