Titlebook: Genetic Programming Theory and Practice XVIII; Wolfgang Banzhaf,Leonardo Trujillo,Bill Worzel Book 2022 The Editor(s) (if applicable) and

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1932-0167 d from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results..978-981-16-8115-8978-981-16-8113-4Series ISSN 1932-0167 Series E-ISSN 1932-0175

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Finding Simple Solutions to Multi-Task Visual Reinforcement Learning Problems with Tangled Program rk the utilization of . (multiple mutations applied simultaneously for offspring creation) and . (multiple actions per state). Several parameterizations are also introduced that potentially penalize the introduction of hitchhikers. Benchmarking over five VizDoom tasks demonstrates that rampant mutat

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,An Exploration of?Exploration: Measuring the?Ability of?Lexicase Selection to?Find Obscure Pathways we find that relaxing lexicase’s elitism with epsilon lexicase can further improve exploration. Both down-sampling and cohort lexicase—two techniques for applying random subsampling to test cases—degrade lexicase’s exploratory capacity; however, we find that cohort partitioning better preserves lex

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,Back to the Future—Revisiting OrdinalGP and Trustable Models After a Decade,erlying system. Although the deployed implementation has been effective, the diversity metric used was data-centric so alternatives have been explored to improve the robustness of ensemble definition. This chapter documents our latest thinking, realizations, and benefits of revisiting OrdinalGP and

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Evolution of the Semiconductor Industry, and the Start of X Law, The human appetite to consume more data puts pressure on the industry. Consumption drives three technology vectors, namely storage, compute, and communication. Under this premise, two thoughts lead to this paper. Firstly, the .?(EoML) [.], where transistor density growth slows down over time. Eithe

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