Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype–phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences.   This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming.  .

Computational Biology -- methods. --- Evolutionary programming (Computer science). --- Genetic programming (Computer science). --- Models, Genetic. --- Genetic programming (Computer science) --- Evolutionary programming (Computer science) --- Engineering & Applied Sciences --- Computer Science --- Computer science. --- Computers. --- Artificial intelligence. --- Application software. --- Computer-aided engineering. --- Electrical engineering. --- Computer Science. --- Theory of Computation. --- Electrical Engineering. --- Artificial Intelligence (incl. Robotics). --- Computer-Aided Engineering (CAD, CAE) and Design. --- Computer Appl. in Arts and Humanities. --- Electric engineering --- Engineering --- CAE --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Informatics --- Science --- Data processing --- Computer programming --- Genetic algorithms --- Information theory. --- Computer engineering. --- Computer aided design. --- Information systems. --- Artificial Intelligence. --- CAD (Computer-aided design) --- Computer-assisted design --- Computer-aided engineering --- Design --- Computers --- Communication theory --- Communication --- Design and construction --- Digital humanities. --- Electrical and Electronic Engineering. --- Digital Humanities. --- Humanities

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype-phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences.   This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming.  

Human sciences (algemeen) --- Electrical engineering --- Applied physical engineering --- Computer science --- Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- toegepaste informatica --- informatica --- sociale wetenschappen --- KI (kunstmatige intelligentie) --- elektrotechniek --- CAD (computer aided design) --- robots

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Nuclear chemistry --- fysicochemie

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Radiochemistry --- Nuclear chemistry --- Radiochimie --- Chimie nucléaire --- Nuclear chemistry. --- Radiochemistry. --- #WSCH:AAS3 --- 541.28 --- Nucleaire chemie --- Radiochemie --- Chemistry, Physical and theoretical --- Chemistry, Nuclear --- Chimie nucléaire

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Thisvolumerecordstheproceedingsofthe?fthEuropeanconferenceonGenetic Programming(EuroGP2002)whichtookplaceinKinsale,IrelandonApril3–5, 2002, continuing an established tradition of yearly meetings among the most prominent researchers on Genetic Programming in Europe and beyond; their proceedings have always been published in the LNCS series by Springer-Verlag. EuroGP began life in Paris in 1998 as an international workshop (April 14– 15, LNCS 1391); a second workshop took place in G¨ oteborg in 1999 (May 26– 27, LNCS 1598). Its ?rst appearance as a conference was in the year 2000 in Edinburgh (April 15–16, LNCS 1802), followed by last year’s conference held at Lake Como (April 18–19, LNCS 2038). Since the beginning, EuroGP has been co-located with a series of specialist workshops on applications of evolutionary algorithms (LNCS 1468, 1596, 1803, and 2037). In keeping with that tradition, the EvoWorkshops were also held in Kinsale this year at the same time (LNCS 2279). Genetic Programming (GP) is a branch of Evolutionary Computation in which populations of computer programs are made to evolve and adapt to so- ing a particular problem or task by a process that draws its inspiration from Biology and Darwinian evolution. GP is a very versatile technique, which has been applied to a wide range of tasks, as a quick inspection of the 32 papers in these proceedings will easily reveal: economics, robotics, engineering, statistics, pharmacology,electronics,and?nancearebutsomeofthedomainsinwhichthey havebeenemployed.AlthoughtherateofapplicationofGPtoproblemsisst- dily growing, this conference is characterized by its concern with the theoretical foundations of GP: investigation of these issues is attaining an ever increasing depth and maturity.

Genetic programming (Computer science) --- Biological Evolution --- Models, Genetic --- Mathematical Computing --- Genetic Processes --- Computing Methodologies --- Models, Biological --- Biological Processes --- Genetic Phenomena --- Models, Theoretical --- Biological Phenomena --- Information Science --- Phenomena and Processes --- Investigative Techniques --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Computer Science --- Engineering & Applied Sciences --- Computer science. --- Software engineering. --- Computer programming. --- Computers. --- Algorithms. --- Artificial intelligence. --- Pattern recognition. --- Computer Science. --- Software Engineering/Programming and Operating Systems. --- Programming Techniques. --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Pattern Recognition. --- Artificial Intelligence (incl. Robotics). --- Computer programming --- Genetic algorithms --- Computer software. --- Optical pattern recognition. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Software, Computer --- Computer systems --- Informatics --- Science --- Computer software engineering --- Engineering --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Cybernetics --- Calculators --- Cyberspace --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Foundations --- Programming