scholarly journals A NEW LINEAR GENETIC PROGRAMMING APPROACH BASED ON STRAIGHT LINE PROGRAMS: SOME THEORETICAL AND EXPERIMENTAL ASPECTS

2009 ◽  
Vol 18 (05) ◽  
pp. 757-781 ◽  
Author(s):  
CÉSAR L. ALONSO ◽  
JOSÉ LUIS MONTAÑA ◽  
JORGE PUENTE ◽  
CRUZ ENRIQUE BORGES
Keyword(s):  
Data Structure ◽  
Genetic Programming ◽  
Computer Programs ◽  
Symbolic Regression ◽  
Programming Approach ◽  
Linear Genetic Programming ◽  
Straight Line ◽  
Structured Representations ◽  
Regression Problems ◽  
Straight Line Programs

Tree encodings of programs are well known for their representative power and are used very often in Genetic Programming. In this paper we experiment with a new data structure, named straight line program (slp), to represent computer programs. The main features of this structure are described, new recombination operators for GP related to slp's are introduced and a study of the Vapnik-Chervonenkis dimension of families of slp's is done. Experiments have been performed on symbolic regression problems. Results are encouraging and suggest that the GP approach based on slp's consistently outperforms conventional GP based on tree structured representations.

scholarly journals Productive corecursion in logic programming

2017 ◽  
Vol 17 (5-6) ◽  
pp. 906-923 ◽  
Author(s):  
EKATERINA KOMENDANTSKAYA ◽  
YUE LI
Keyword(s):  
Data Structure ◽  
Logic Programming ◽  
State Of The Art ◽  
Logic Program ◽  
Stream Processing ◽  
The Internet ◽  
Logic Programs ◽  
Algorithmic Solution ◽  
Undecidable Property ◽  
Turing Complete

AbstractLogic Programming is a Turing complete language. As a consequence, designing algorithms that decide termination and non-termination of programs or decide inductive/coinductive soundness of formulae is a challenging task. For example, the existing state-of-the-art algorithms can only semi-decide coinductive soundness of queries in logic programming for regular formulae. Another, less famous, but equally fundamental and important undecidable property is productivity. If a derivation is infinite and coinductively sound, we may ask whether the computed answer it determines actually computes an infinite formula. If it does, the infinite computation is productive. This intuition was first expressed under the name of computations at infinity in the 80s. In modern days of the Internet and stream processing, its importance lies in connection to infinite data structure processing. Recently, an algorithm was presented that semi-decides a weaker property – of productivity of logic programs. A logic program is productive if it can give rise to productive derivations. In this paper, we strengthen these recent results. We propose a method that semi-decides productivity of individual derivations for regular formulae. Thus, we at last give an algorithmic counterpart to the notion of productivity of derivations in logic programming. This is the first algorithmic solution to the problem since it was raised more than 30 years ago. We also present an implementation of this algorithm.

Genetic Programming Using a Turing-Complete Representation

2005 ◽  
pp. 61-81 ◽  
Author(s):  
Taro Yabuki ◽  
Hitoshi Iba
Keyword(s):  
Genetic Programming ◽  
Evolutionary Computing ◽  
Recurrent Network ◽  
Complete Representation ◽  
Representation Scheme ◽  
Turing Complete ◽  
General Method

In this chapter, a new representation scheme for Genetic Programming (GP) is proposed. We need a Turing-complete representation for a general method of generating programs automatically; that is, the representation must be able to express any algorithms. Our representation is a recurrent network consisting of trees (RTN), which is proved to be Turing-complete. In addition, it is applied to the tasks of generating language classifiers and a bit reverser. As a result, RTN is shown to be usable in evolutionary computing.

scholarly journals Evolving continuous optimisers from scratch

2021 ◽  
Author(s):  
Michael A. Lones
Keyword(s):  
Genetic Programming ◽  
Search Space ◽  
General Purpose ◽  
Problem Types ◽  
Broad Variety ◽  
Turing Complete

AbstractThis work uses genetic programming to explore the space of continuous optimisers, with the goal of discovering novel ways of doing optimisation. In order to keep the search space broad, the optimisers are evolved from scratch using Push, a Turing-complete, general-purpose, language. The resulting optimisers are found to be diverse, and explore their optimisation landscapes using a variety of interesting, and sometimes unusual, strategies. Significantly, when applied to problems that were not seen during training, many of the evolved optimisers generalise well, and often outperform existing optimisers. This supports the idea that novel and effective forms of optimisation can be discovered in an automated manner. This paper also shows that pools of evolved optimisers can be hybridised to further increase their generality, leading to optimisers that perform robustly over a broad variety of problem types and sizes.

Distributed Modeling Of Building Systems Through Cyber-Physical Integration

2019 ◽  
pp. 12-17
Keyword(s):  
Data Structure ◽  
Operating Conditions ◽  
Physical Models ◽  
Distributed Model ◽  
Physical Processes ◽  
Distributed Modeling ◽  
Distributed Models ◽  
Operating Modes ◽  
Building Systems ◽  
Important Practical Application

This article describes the proposed approaches to creating distributed models that can, with given accuracy under given restrictions, replace classical physical models for construction objects. The ability to implement the proposed approaches is a consequence of the cyber-physical integration of building systems. The principles of forming the data structure of designed objects and distributed models, which make it possible to uniquely identify the elements and increase the level of detail of such a model, are presented. The data structure diagram of distributed modeling includes, among other things, the level of formation and transmission of signals about physical processes inside cyber-physical building systems. An enlarged algorithm for creating the structure of the distributed model which describes the process of developing a data structure, formalizing requirements for the parameters of a design object and its operating modes (including normal operating conditions and extreme conditions, including natural disasters) and selecting objects for a complete group that provides distributed modeling is presented. The article formulates the main approaches to the implementation of an important practical application of the cyber-physical integration of building systems - the possibility of forming distributed physical models of designed construction objects and the directions of further research are outlined.

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