scholarly journals Four problems for which a computer program evolved by genetic programming is competitive with human performance

2002 ◽  
Author(s):  
J.R. Koza ◽  
F.H. Bennett ◽  
D. Andre ◽  
M.A. Keane
Keyword(s):  
Genetic Programming ◽  
Computer Program ◽  
Human Performance

scholarly journals GAPS: A Genetic Programming System

2003 ◽  
Vol 12 (02) ◽  
pp. 187-206 ◽  
Author(s):  
Du Zhang ◽  
Michael D. Kramer
Keyword(s):  
Genetic Programming ◽  
Computer Program ◽  
Evolutionary Computation ◽  
Computer Programs ◽  
Initial Problem ◽  
Evolution Process ◽  
Programming System ◽  
Problem Statement ◽  
Termination Criteria

One of the major approaches in the field of evolutionary computation is genetic programming. Genetic programming tackles the issue of how to automatically create a computer program for a given problem from some initial problem statement. The goal is accomplished by genetically breeding a population of computer programs in terms of genetic operations. In this paper, we describe a genetic programming system called GAPS. GAPS has the following features: (1) It implements the standard generational algorithm for genetic programming with some refinement on controlling introns growth during evolution process and improved termination criteria. (2) It includes an extensible language tailored to the needs of genetic programming. And (3) It is a complete, standalone system that allows for genetic programming tasks to be carried out without requiring other tools such as compilers. Results with GAPS have been satisfactory.

Simultaneous Interpreting (SI): the Holy Grail of Artificial Intelligence – An SI Practitioner’s Perspective

2017 ◽  
Vol 62 (2) ◽  
Author(s):  
Ailing Zhang
Keyword(s):  
Artificial Intelligence ◽  
Computer Program ◽  
Image Recognition ◽  
Human Performance ◽  
Rapid Progress ◽  
Holy Grail ◽  
Simultaneous Interpreting ◽  
The Past ◽  
World Class ◽  
Near Future

AbstractArtificial Intelligence (AI) has been become a household expression, especially in the past couple of years thanks to Google’s AI Computer program AlphaGo defeating a couple of world-class Go masters from Korea and China. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Although it is unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the near future, experts forecast that rapid progress in the field of specialized AI will continue, with machines reaching and exceeding human performance on an increasing number of tasks. Simultaneous interpreting, being among the most complex of human cognitive/linguistic activities, with all the associated ergonomic elements, has been discussed profusely as one of the most likely to be taken over by AI in a couple of years. Given that so much has to be there simultaneously, i. e. anticipation, restoration of the implicit-explicit balance, and communicative re-packaging (‘re-ostension’

scholarly journals A Combination of Palmer Algorithm and Gupta Algorithm for Scheduling Problem in Apparel Industry

2021 ◽  
Vol 11 (1) ◽  
pp. 1-12
Author(s):  
Cecilia E. Nugraheni ◽  
Luciana Abednego ◽  
Maria Widyarini
Keyword(s):  
Genetic Programming ◽  
Computer Program ◽  
Production Scheduling ◽  
Textile Industry ◽  
Flow Shop ◽  
Apparel Industry ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Shop Scheduling

The apparel industry is a class of textile industry. Generally, the production scheduling problem in the apparel industry belongs to Flow Shop Scheduling Problems (FSSP). There are many algorithms/techniques/heuristics for solving FSSP. Two of them are the Palmer Algorithm and the Gupta Algorithm. Hyper-heuristic is a class of heuristics that enables to combine of some heuristics to produce a new heuristic. GPHH is a hyper-heuristic that is based on genetic programming that is proposed to solve FSSP [1]. This paper presents the development of a computer program that implements the GPHH. Some experiments have been conducted for measuring the performance of GPHH. From the experimental results, GPHH has shown a better performance than the Palmer Algorithm and Gupta Algorithm.

Cooperation Between Agents to Evolve Complete Programs

2011 ◽  
pp. 213-228 ◽  
Author(s):  
Ricardo Aler ◽  
David Camacho ◽  
Alfredo Moscardini
Keyword(s):  
Genetic Programming ◽  
Computer Program ◽  
System Approach ◽  
Multiagent System ◽  
Computer Programs ◽  
Main Body ◽  
Programming Paradigm

In this paper, we present a multiagent system approach with the purpose of building computer programs. Each agent in the multiagent system will be in charge of evolving a part of the program, which in this case, can be the main body of the program or one of its different subroutines. There are two kinds of agents: the manager agent and the genetic programming (GP) agents. The former is in charge of starting the system and returning the results to the user. The GP agents include skills for evolving computer programs, based on the genetic programming paradigm. There are two sorts of GP agents: some can evolve the main body of the program and the others evolve its subroutines. Both kinds of agents cooperate by telling each other their best results found so far, so that the search for a good computer program is made more efficient. In this paper, this multiagent approach is presented and tested empirically.

A general computer program for the extended plate overlap algorithm

1978 ◽  
Vol 48 ◽  
pp. 287-293 ◽  
Author(s):  
Chr. de Vegt ◽  
E. Ebner ◽  
K. von der Heide
Keyword(s):  
Computer Program ◽  
Simultaneous Determination ◽  
General Computer Program ◽  
General Computer

In contrast to the adjustment of single plates a block adjustment is a simultaneous determination of all unknowns associated with many overlapping plates (star positions and plate constants etc. ) by one large adjustment. This plate overlap technique was introduced by Eichhorn and reviewed by Googe et. al. The author now has developed a set of computer programmes which allows the adjustment of any set of contemporaneous overlapping plates. There is in principle no limit for the number of plates, the number of stars, the number of individual plate constants for each plate, and for the overlapping factor.

Structures and crystallization of vacuum-deposited amorphous Se and Sb films

1990 ◽  
Vol 48 (4) ◽  
pp. 140-141
Author(s):  
Makoto Shiojiri ◽  
Toshiyuki Isshiki ◽  
Tetsuya Fudaba ◽  
Yoshihiro Hirota
Keyword(s):  
Monte Carlo ◽  
Electron Microscope ◽  
Monte Carlo Method ◽  
Computer Program ◽  
Radial Distribution ◽  
Film Formation ◽  
Amorphous State ◽  
Two Dimensional ◽  
Amorphous Films ◽  
Binding Condition

In hexagonal Se crystal each atom is covalently bound to two others to form an endless spiral chain, and in Sb crystal each atom to three others to form an extended puckered sheet. Such chains and sheets may be regarded as one- and two- dimensional molecules, respectively. In this paper we investigate the structures in amorphous state of these elements and the crystallization.HRTEM and ED images of vacuum-deposited amorphous Se and Sb films were taken with a JEM-200CX electron microscope (Cs=1.2 mm). The structure models of amorphous films were constructed on a computer by Monte Carlo method. Generated atoms were subsequently deposited on a space of 2 nm×2 nm as they fulfiled the binding condition, to form a film 5 nm thick (Fig. 1a-1c). An improvement on a previous computer program has been made as to realize the actual film formation. Radial distribution fuction (RDF) curves, ED intensities and HRTEM images for the constructed structure models were calculated, and compared with the observed ones.

The limits of human performance

2008 ◽  
Vol 44 ◽  
pp. 11-26 ◽  
Author(s):  
Ralph Beneke ◽  
Dieter Böning
Keyword(s):  
Human Performance ◽  
Safety Margin ◽  
Afferent Input ◽  
Metabolic Energy ◽  
Human Organism ◽  
Mechanical Resistance ◽  
As Doping ◽  
Gene And Protein Expression ◽  
Underlying Mechanisms ◽  
Biochemical Research

Human performance, defined by mechanical resistance and distance per time, includes human, task and environmental factors, all interrelated. It requires metabolic energy provided by anaerobic and aerobic metabolic energy sources. These sources have specific limitations in the capacity and rate to provide re-phosphorylation energy, which determines individual ratios of aerobic and anaerobic metabolic power and their sustainability. In healthy athletes, limits to provide and utilize metabolic energy are multifactorial, carefully matched and include a safety margin imposed in order to protect the integrity of the human organism under maximal effort. Perception of afferent input associated with effort leads to conscious or unconscious decisions to modulate or terminate performance; however, the underlying mechanisms of cerebral control are not fully understood. The idea to move borders of performance with the help of biochemicals is two millennia old. Biochemical findings resulted in highly effective substances widely used to increase performance in daily life, during preparation for sport events and during competition, but many of them must be considered as doping and therefore illegal. Supplements and food have ergogenic potential; however, numerous concepts are controversially discussed with respect to legality and particularly evidence in terms of usefulness and risks. The effect of evidence-based nutritional strategies on adaptations in terms of gene and protein expression that occur in skeletal muscle during and after exercise training sessions is widely unknown. Biochemical research is essential for better understanding of the basic mechanisms causing fatigue and the regulation of the dynamic adaptation to physical and mental training.

1880: Assessment of Basic Human Performance Resources Predicts Performance of Ureterorenoscopy in Human Cadavers

2004 ◽  
Vol 171 (4S) ◽  
pp. 496-497
Author(s):  
Edward D. Matsumoto ◽  
George V. Kondraske ◽  
Lucas Jacomides ◽  
Kenneth Ogan ◽  
Margaret S. Pearle ◽  
...  
Keyword(s):  
Human Performance ◽  
Human Cadavers
Sign in / Sign up

Export Citation Format

Share Document