Titlebook: Genetic Programming and Data Structures; Genetic Programming W. B. Langdon Book 1998 Springer Science+Business Media New York 1998 Schedul

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https://doi.org/10.1007/978-1-4615-5731-9Scheduling; algorithms; artificial intelligence; automatic programming; code; data structure; data structu

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Introduction,hilst this is highly successful, it requires limited interaction between components. The building block hypothesis [Goldberg, 1989] states the same is true for artificial evolution. While doubts concerning the building block hypothesis have been expressed in general (e.g. [Beyer, 1995]) and for gene

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Advanced Genetic Programming Techniques,ter chapters, Sections 3.2 onwards describe more specialist techniques, some of which are introduced into GP. In later chapters, where we first use one of these concepts, we will refer back to the appropriate subsection within Section 2.3.2 or 3.2–3.9. (There is also a glossary in Appendix B).

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Evolving a Queue,ntil a service provider is able to process it. Data for each new request enters the queue at its rear and waits until data in front of it has been processed and removed from the front of the queue. When it reaches the front of the queue, it too is processed and removed from the front queue. Queues a

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Evolving a List,rogramming (GP) to evolve a list data structure from basic primitives. There are many ways in which a list can be implemented ([Aho et al., 1987] suggest three fundamentally different ways, each of which has many variations) but GP is able to co-evolve all the list components so they form a single w

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Problems Solved Using Data Structures,e, 1995; Jannink, 1994] shows GP can automatically create programs which explicitly use directly addressable (indexed) memory to solve problems and Chapters 4, 5 and 6 demonstrate that GP can automatically generate abstract data structures such as stacks, queues and lists. In this chapter we show th

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