Genetic Programming: Biologically Inspired Computation that Creatively Solves Non-Trivial Problems

نویسندگان

  • John R. Koza
  • Forrest H. Bennett
  • David Andre
  • Martin A. Keane
  • Arthur Samuel
چکیده

This paper describes a biologically inspired domain-independent technique, called genetic programming, that automatically creates computer programs to solve problems. Starting with a primordial ooze of thousands of randomly created computer programs, genetic programming progressively breeds a population of computer programs over a series of generations using the Darwinian principle of natural selection, recombination (crossover), mutation, gene duplication, gene deletion, and certain mechanisms of developmental biology. The technique is illustrated by applying it to a non-trivial problem involving the automatic synthesis (design) of a lowpass lter circuit. The evolved results are competitive with human-produced solutions to the problem. In fact, four of the automatically created circuits exhibit human-level creativity and inventiveness, as evidenced by the fact that they correspond to four inventions that were patented between 1917 and 1936.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Genetic Programming: Biologically Inspired Computation that Exhibits Creativity in Solving Non-Trivial Problems

This paper describes a biologically inspired domain-independent technique, called genetic programming, that automatically creates computer programs to solve problems. We argue that the field of design is a useful testbed for determining whether an automated technique can produce results that are competitive with human-produced results. We present several results that are competitive with the pr...

متن کامل

Shuffled Frog-Leaping Programming for Solving Regression Problems

There are various automatic programming models inspired by evolutionary computation techniques. Due to the importance of devising an automatic mechanism to explore the complicated search space of mathematical problems where numerical methods fails, evolutionary computations are widely studied and applied to solve real world problems. One of the famous algorithm in optimization problem is shuffl...

متن کامل

On the optimization of Dombi non-linear programming

Dombi family of t-norms includes a parametric family of continuous strict t-norms, whose members are increasing functions of the parameter. This family of t-norms covers the whole spectrum of t-norms when the parameter is changed from zero to infinity. In this paper, we study a nonlinear optimization problem in which the constraints are defined as fuzzy relational equations (FRE) with the Dombi...

متن کامل

Natural Selection of Asphalt Mix Stiffness Predictive Models with Genetic Programming

Genetic Programming (GP) is a systematic, domain-independent evolutionary computation technique that stochastically evolves populations of computer programs to perform a user-defined task. Similar to Genetic Algorithms (GA) which evolves a population of individuals to better ones, GP iteratively transforms a population of computer programs into a new generation of programs by applying biologica...

متن کامل

الگوریتم بهینه یابی جفت گیری زنبورهای عسل ( HBMO ) در حل مسائل بهینه سازی

 Over the last decade, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Ease of use and broad applicability may be considered as the primary reasons for their success. The honey-bee mating process has been considered as a typical swarm-based approach to optimization, i...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999