D. A. Gustafson, W. A. Barrett, R. M. Bates, and J. D. Couch. Compile construction: Theory and Practice. Science Research Assoc, Inc., 1986. Home/Search Document Not in Database Summary Related Articles Check |
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Software Project Effort Estimation Using Genetic Programming - Shan, McKay, Lokan, Essam (Correct)
....execution. Too general a language also obviates one of the most important advantages of employing a grammar: constraining search space. This trade off needs to be carefully considered. Two languages were used for evolving software development effort estimation programs. The context free grammars [11, 12] for these languages are in Figure 1. Each of the grammars describes a language, whose expressions may be viewed as mathematic models with See http: www.isbsg.org.au Variable Name Description Numeric Variable: effort Total project effort (hours) size Project size (Function Points) team ....
D. A. Gustafson, W. A. Barrett, R. M. Bates, and J. D. Couch. Compile construction: Theory and Practice. Science Research Assoc, Inc., 1986.
Inductive Bias and Genetic Programming - Whigham (1995) (13 citations) (Correct)
.... and Learning Given a language to express the solution to a problem, bias is the set of all factors that influence the form of each program (hypothesis) 7] Bias may describe both the possible types of programs that may be generated, 1 An introduction to context free grammars may be found in [8]. and the way in which these structures can be modified. Two important components of bias are strength and correctness: Bias may be categorised as strong or weak. A strong bias focuses upon a small number of possible hypothesis, whereas a weak bias allows a relatively large number of possible ....
D.A.Gustafson W.A. Barrett, R.M. Bates and J.D.Couch. Compiler Construction: Theory and Practice. Science Research Assoc, Inc., 1986.
Grammatically-based Genetic Programming - Whigham (1995) (25 citations) (Correct)
....tree from the grammar. We also describe extensions to this form that allow bias to be learnt as the evolution of a solution proceeds. The system will be referred to as context free grammar genetic programming, or CFG GP. 1. 3 Context Free Grammars An introduction to grammars may be found in [W.A. Barrett and J.D.Couch, 1986] A context free grammar is a four tuple (N; P ; P; S) where N is the nonterminal 1 alphabet, P is the terminal alphabet, P is the set of productions and S is the designated start symbol. The productions are of the form x y, where x 2 N , y 2 f P [Ng . Productions of the form x ....
D.A.Gustafson W.A. Barrett, R.M. Bates and J.D.Couch. Compiler Construction: Theory and Practice. Science Research Assoc, Inc., 1986.
A Schema Theorem for Context-Free Grammars - Whigham (1995) (45 citations) (Correct)
....satisfies the issues of closure and typing that have occurred with genetic programming (GP) The use of a formal grammatical structure allows a schema, defined by the derivation trees, to represent the sentences (programs) of the language. 1 An introduction to formal languages may be found in [1]. 2. Grammatical Genetic Learning An evolutionary framework for learning strings defined by the language L, and represented by the context free grammar G, may be stated as: 1. Create an initial random population L i (G) ae L(G) with derivation trees D i (G) ae D(G) 2. While termination ....
D.Barrett, R. Bates, D. Gustafson, and J.Couch, Compiler Construction: Theory and Practice. Science Research Assoc, Inc., 1986.
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