A Linguistic Theory of Translation (Language and Language - download pdf or read online

By J.C. Catford

Show description

Read or Download A Linguistic Theory of Translation (Language and Language Learning) PDF

Similar intelligence & semantics books

Paul P. Wang, Da Ruan, Etienne E. Kerre's Fuzzy Logic: A Spectrum of Theoretical & Practical Issues PDF

This booklet solely surveys the lively on-going study of the present adulthood of fuzzy common sense over the past 4 many years. Many international leaders of fuzzy common sense have enthusiastically contributed their top study effects into 5 theoretical, philosophical and basic sub components and 9 exact purposes, together with PhD dissertations from international category universities facing state of the art learn components of bioinformatics and geological technology.

Read e-book online Algorithms for Reinforcement Learning PDF

Reinforcement studying is a studying paradigm all for studying to manage a method in order to maximise a numerical functionality degree that expresses a long term target. What distinguishes reinforcement studying from supervised studying is that in simple terms partial suggestions is given to the learner concerning the learner's predictions.

Intelligent Computing and Applications: Proceedings of the - download pdf or read online

The assumption of the first overseas convention on clever Computing and purposes (ICICA 2014) is to convey the learn Engineers, Scientists, Industrialists, students and scholars jointly from in and all over the world to offer the on-going examine actions and for that reason to inspire learn interactions among universities and industries.

Additional resources for A Linguistic Theory of Translation (Language and Language Learning)

Sample text

This method is called Hierarchical Multi-Agent Genetic Algorithm (HMAGA). In HMAGA, the size of initial population equals to the number of the macro-agents in the lowest layer. For convenience, each macroagent sets the same values of parameters of MAGA. The cooperation behavior used in HMAGA synthesizes two macro-agents in the ith layer into a new macroagent in the (i-1)th layer, which is given below. f 00 f11 f12 f 21 f 22 f 23 f 24 f31 f32 f33 f34 f35 f36 f37 f38 Fig. 3 The hierarchical decomposition of Resenbrock function 40 J.

In HMAGA, the size of initial population equals to the number of the macro-agents in the lowest layer. For convenience, each macroagent sets the same values of parameters of MAGA. The cooperation behavior used in HMAGA synthesizes two macro-agents in the ith layer into a new macroagent in the (i-1)th layer, which is given below. f 00 f11 f12 f 21 f 22 f 23 f 24 f31 f32 f33 f34 f35 f36 f37 f38 Fig. 3 The hierarchical decomposition of Resenbrock function 40 J. Liu, W. Zhong, and L. Jiao Suppose MA1 and MA2 are synthesized into MA, then we have MA ( x s ) ← MA1 ( x s ) ∪ MA2 ( x s ) , MA ( f s ( x s ) ) ← MA1 ( f s ( x s ) ) ∪ MA2 ( f s ( x s ) ) .

Lsize × Lsize ⎝ ⎠ Multi-Agent Evolutionary Model for Global Numerical Optimization 23 Suppose that the energy of an agent lattice, L, is equal to Energy(L), which is determined by, Energy ( L) = max {Energy ( Li , j ) i , j = 1, Thus ∀L ∈ L, E E , Lsize } (20) ≤ Energy ( L) ≤ E 1 . Therefore, L can be partitioned into a col- lection of nonempty subsets {Li i = 1, 2, ,| E |} , where { Li = L L ∈ L and Energy ( L) = E i ∑ |E | i =1 | Li |=| L |; Li ≠ ∅, ∀i ∈ {1, 2, Li ∩ Lj = ∅, ∀i ≠ j; } ,| E |}; |E | ∪ i =1 Li = L (21) (22) L1 consists of all the agent lattices whose energies are E1.

Download PDF sample

A Linguistic Theory of Translation (Language and Language Learning) by J.C. Catford


by Richard
4.5

Rated 4.89 of 5 – based on 23 votes