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📄 readme.txt

📁 标准的GP源代码,由Andy Singleton维护
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*************************************************************************GPQUICKA simple Genetic Programming system in C++Version 2, released 2/12/94************************************************************************* Copyright Andy Singleton, 1993,1994 This code is released for non-commercial use only For questions or upgrades contact:    Andy Singleton    Creation Mechanics, Inc.    PO Box 248, Peterborough, NH 03458    Internet: p00396@psilink.com    Compuserve: 73313,757    Phone: (603) 563-7757 Further documentation appears in the associated Byte Magazine article "Genetic Programming with C++", February, 1994*************************************************************************Packing List*************************************************************************Source Files:     CHROME.H        // Core object definitions and GP code     CHROME.CPP     PRIMITIV.H              // Standard GP primitive functions     PRIMITIV.CPP     SELECTOR.H       // A utility GA fitness selector object     SELECTOR.CPP     PCH.H           // Standard headers for "precompiled headers"     SSPROB.CPP      // A "Simple Symbolic Regression" sample problem					 // Contains "main" and most user modified sections     ANTPROB.CPP     // The "Artificial Ant" sample problem     SANTAFE.TRL     // A trail of food required by the artificial antOther Files:     README.TXT      // This fileThe DOS package may also include     GPUICK.EXE                  // DOS executable of SSPROB     GPQUICK.PRJ                 // Borland project fileOptional Files (at McGraw Hill's option)     BYTEGP.PS,TXT,WRI      // The associated magazine article			    // It is a general introduction to GP,			    // but it contains some helpful technical doc*************************************************************************Instructions*************************************************************************To Make:     Compile CHROME.CPP, PRIMITIV.CPP, SELECTOR.CPP and SSPROB.CPP	 Link with SSPROB as the main     You can substitute ANTPROB or any compatible problem for SSPROBThe code is ANSI C++, but you may encounter a few portability issues.It was originally compiled with 16 bit Borland C++ under DOS and MS Windows.Configure for UNIX by uncommenting "#define UNIX" in file PCH.HI will share alterations for other compilers and OS as users provide them.Runtime Behavior:     The sample problem, SSPROB, will attempt to evolve an expressionequivalent to John*(George-Paul)+2.5*Ringo.  Every 5 seconds or 1000expression evaluations, it will list to the console the best expressionfound so far. It will run for 80,000 evaluations, until it finds theright answer, or (under DOS) until you hit a key.	The sample problem ANTPROB will attempt to evolve an artificial antwhich can traverse the trail of food.  The ant moves across a 32x32 grid,and it can sense food immediately ahead, move forward, or turn.  As theproblem runs, it will display the best ant by the amount of food found.After the ant finds all of the food (89 pieces on the Santa Fe trail), orafter 25,000 generates, the problem terminates and prints the path of thebest ant to file "RESULT.TXT".  This is a replication of the problemdescribed by John Koza in "A-Life II" and "Genetic Programming".Exercises:	 You can evolve more interesting or useful behavior by editing the problems	 provide to create your own GP problems.Please: If you develop an interesting problem, send me a copy.Technical Details:     GPQUICK as provided here uses a steady state GA, tournament selectionthree types of mutation, and subtree crossover.    It uses tournament selection with a tournament size of six, and a"kill tournament" size of 2.  It uses a node mutation (switching a nodefor another node of the same arity), constant mutation (small adjustmentsto constant values) and shrink mutation (promote a sub-subtree to replace asubtree) 10% of the time each, a copy with reevaluation on new cases 10% ofthe time, and subtree crossover 70% of the time.  The default populationsize is 2000.	GPQUICK also supports both crossover and mutation "annealing" operations,which replace a parent instead of reproducing into a target site.  These canmake a small population look big, improve hill climbing, and reduce convergence.    The GP representation is a linear array of 2 byte nodes, suggested as"linear prefix jump table" by Mike Keith.  This version also contains theFASTEVAL option for fast eval calls.    The function argument/return values can be any floating point number.Numeric constants must be integers from -128 to +127.  Unless you adjust theconstants with hill-climbing methods, the precise constant values are not important.    GPQUICK features an elegant object architecture with function(Function), program (Chrome), GA (Pop) and problem (Problem) classes.*************************************************************************Improvements in version 2*************************************************************************In atonement for past sins, I am offering an updated version of GPQUICK.The new version of GPQUICK has the following improvements:Several bug fixesUnified UNIX/DOS/ANSI sourceMore extensible object structureFitnessValue object for carrying problem specific fitness information    (in response to popular demand from the GP mailing list)Streamlined Problem filesImproved function constructorStandard primitive library, including a working IF and IFLTE.Annealing2 more mutationsArtificial Ant problem*************************************************************************For More GP fun*************************************************************************DOODLE GARDEN, a GP toy and "Grow your own" screen saver, is softwarewhich allows you to experiment interactively with a wide variety ofprimitives and genetic operators.  Doodle Garden is an MS Windowspackage which allows the user to evolve programs that draw pictures,or "doodles" by mutating and crossing other doodles.  Doodle Gardenis available from Creation Mechanics for $39.00.Creation Mechanics will provide a professional GP system called GP-GIM(Genetic Programming - Genetic Induction Machine).  If you use the evaluation macros, GPQUICK problems should be source code compatiblewith GP-GIM problems.GP-GIM includes:* Built in Problems for regression, classification, and selection from data* Problems plug in at runtime as DLL's* Rich set of primitive functions, with many add in function packs* Numerous GA options, operators, and over 50 parameters* Meta-GA for automated primitive selection, parameter selection and  generalization* Subroutine defining structures, constrained crossover, fixed roots* Interactive user interface* Runtime libraries for using and distributing the resulting code* High speed implementation* "Desktop Supercomputing" architecture linking a network of PC's or workstations into a parallel GP machine.  Rack mounted clusters are alsoavailable.For more information, contact Creation Mechanics at the phone numberand address listed on the top of this file.

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