Titlebook: Genetic Programming Theory and Practice XIII; Rick Riolo,W.P.‘Worzel,Arthur Kordon Book 2016 Springer International Publishing Switzerland

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GP As If You Meant It: An Exercise for Mindful Practice,g software developers, it’s an exercise designed to help participants hone their skills through mindful practice. Its intent is to surface certain unquestioned habits common in our field: to make the participants painfully aware of the tacit . for certain GP algorithm design decisions they may other

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Malleable

Highly Accurate Symbolic Regression with Noisy Training Data,ced commercial packages, has become an issue for early adopters. Users expect to have the correct formula returned, especially in cases with zero noise and only one basis function with minimally complex grammar depth..At a minimum, users expect the response surface of the SR tool to be easily unders

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BLA

The Evolution of Everything (EvE) and Genetic Programming,essors are sensors that continuously collect data. By 2020, it is projected that?there may be more than 20 billion (1000 million) devices connected to the Internet. Collectively these devices are called the Internet of Things (IoT) or the Internet of Everything (IoE). The sheer volume of the data th

螢火蟲

Lexicase Selection for Program Synthesis: A Diversity Analysis,rmance on test cases, considered in random order. When used as the parent selection method in genetic programming, lexicase selection has been shown to provide significant improvements in problem-solving power. In this chapter we investigate the reasons for the success of lexicase selection, focusin

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Behavioral Program Synthesis: Insights and Prospects,-output mapping. The number of passed tests, or the total error in continuous domains, is a natural objective measure of a program’s performance and a common yardstick when experimentally comparing algorithms. In GP, it is also by default used to . the evolutionary search process. An assumption that

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Using Graph Databases to Explore the Dynamics of Genetic Programming Runs,ften obscure or completely mask the profusion of specific selections,?crossovers, and mutations that are ultimately responsible for the aggregate behaviors we’re interested in. In this chapter we take a different approach and use the Neo4j graph database system to record and analyze the entire genea