Grammatically-based Genetic Programming
نویسنده
چکیده
The genetic programming (GP) paradigm is a functional approach to inductively forming programs. The use of natural selection based on a tness function for reproduction of the program population has allowed many problems to be solved that require a non-xed representation. Attempts to extend GP have focussed on typing the language to restrict crossover and to ensure legal programs are always created. We describe the use of a context free grammar to deene the structure of the initial language and to direct crossover and mutation operators. The use of a grammar to specify structure in the hypothesis language allows a clear statement of inductive bias and control over typing. Modifying the grammar as the evolution proceeds is used as an example of learnt bias. This technique leads to declarative approaches to evolutionary learning, and allows elds such as incre-mental learning to be incorporated under the same paradigm.
منابع مشابه
Inductive Bias and Genetic Programming
Many engineering problems may be described as a search for one near optimal description amongst many possibilities, given certain constraints. Search techniques, such as genetic programming, seem appropriate to represent many problems. This paper describes a grammatically based learning technique , based upon the genetic programming paradigm, that allows declarative biasing and modiies the bias...
متن کاملUsing Genetic Programming to Synthesize Monotonic Stochastic Processes
The automatic synthesis of stochastic concurrent processes is investigated. We use genetic programming to automatically evolve a set of stochastic π-calculus expressions that generate execution behaviour conforming to some supplied target behaviour. We model the stochastic π-calculus in a grammatically-guided genetic programming system, and we use an efficient interpreter based on the SPIM abst...
متن کاملBedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming
Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...
متن کاملA Genetic Programming-based Scheme for Solving Fuzzy Differential Equations
This paper deals with a new approach for solving fuzzy differential equations based on genetic programming. This method produces some trial solutions and seeks the best of them. If the solution cannot be expressed in a closed analytical form then our method produces an approximation with a controlled level of accuracy. Furthermore, the numerical results reveal the potential of the proposed appr...
متن کاملBedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming
Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...
متن کامل