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Evolvica 0.6.3.2
Evolvica is a Java evolutionary computation framework. more>>
Evolvica is a Java Framework for evolutionary algorithms. It is the successor of eaLib, which has been developed at the Department of Electronic Circuits & Systems of the Technical University of Ilmenau, Germany from 2000 to 2002. The development on eaLib has been stopped and focuses now on Evolvica. However, eaLib is still available here.
There were quite some things in eaLib that were too complicated to be used. Therefore efforts have been undertaken to simplify the eaLib structure while preserving its flexibility. In addition the internal structure of genetic operators have changed in a way to support a creation of algorithms via a graphical user interface.
The goal for the future is to provide a complete development environment for evolutionary algorithms, including visual algorithm composer, Java editor, debugger and visual result analysis. This would be quite a lot of work but fortunately there is no need to invent the wheel for the 733rd time. Evolvica is based on the Eclipse Platform and uses the foundations provided by this great toolkit. All the Java features (source code editor, debugger and so on) originate from the Eclipse project.
Please note that the current state of the project is still classified as experimental. The version that you can download does not have production quality, it is a functional prototype that is still in some kind of an alpha-state. Several things are working, several others may not as expected. But you are free to try and find out for yourself and you are invited to share your experiences with others on the Evolvica user forum.
<<lessThere were quite some things in eaLib that were too complicated to be used. Therefore efforts have been undertaken to simplify the eaLib structure while preserving its flexibility. In addition the internal structure of genetic operators have changed in a way to support a creation of algorithms via a graphical user interface.
The goal for the future is to provide a complete development environment for evolutionary algorithms, including visual algorithm composer, Java editor, debugger and visual result analysis. This would be quite a lot of work but fortunately there is no need to invent the wheel for the 733rd time. Evolvica is based on the Eclipse Platform and uses the foundations provided by this great toolkit. All the Java features (source code editor, debugger and so on) originate from the Eclipse project.
Please note that the current state of the project is still classified as experimental. The version that you can download does not have production quality, it is a functional prototype that is still in some kind of an alpha-state. Several things are working, several others may not as expected. But you are free to try and find out for yourself and you are invited to share your experiences with others on the Evolvica user forum.
Download (31.3MB)
Added: 2005-04-01 License: Artistic License Price:
1673 downloads
Evocosm 3.2.0
Evocosm is a C++ Framework for Evolutionary Computing library. more>>
Evocosm is a C++ Framework for Evolutionary Computing library.
Evocosm is a set of classes that abstract the fundamental components of an evolutionary algorithm. Ill list the components here with a bit of introduction; you can review the details of the classes by downloading the code archives or by reviewing the online documentation (see the menu at the articles beginning for code and documentation links.)
All class documentation was generated from source code comments using doxygen. These docs have not been thoroughly proofread, so they may contain a few typos and minor errors. Self-publishing has taught me the value of a good proofreader.
Evolutionary algorithms come in a variety of shapes and flavors, but at their core, they all share certain characteristics: populations that reproduce and mutate through a series of generations, producing future generations based on some measure of fitness. An amazing variety of algorithms can be built on that general framework, which leads me to construct a set of core classes as the basis for future applications.
The classes include:
Random Numbers
Evocosm relies on the code in The Twisted Road to to Randomness for random number generation. The Mersenne Twister algorithm is particularly well-suited to evolutionary algorithms, based on its long period, granularity, "randomness", and speed. As of the 2.1.0 release of libevocosm, the mtprng class resides in libcoyote, and not libevocosm as it did earlier. This means that any program using libevocosm must also link against libcoyote.
Validation
To validate function arguments, Evocosm uses the code I describe in Beyond Assert; this code is part of libcoyote. Any program using libevocosm must also link against libcoyote.
Floating- Point Chromosomes
Evcosom supports the crossover and mutation of IEEE-754 floating-point numbers, using an algorithm I invented in the mid-1990s. This topic is covered in detail here.
Roulette Wheels
The roulette_wheel class implements the concept of a "software roulette wheel" for Evocosm. This is a tool for natural selection, wherein the fitness of an organism determines the width of its "slot" on an imaginary roulette wheel.
Organisms
Think of an "organism" as an answer to a problem posed by a fitness landscape; "genes" define its behavior and an associated fitness value is assigned by an evocosm during testing. Evocosm provides the freedom to define organisms as almost anything: bit strings, floating-point numbers, finite state machines, LISP programs, or external robots controlled via radio waves. In A Complexity of Options, I used an Evocosm-derived GA to determine the gcc options that produce the faster code.
Fitness Landscapes
A "fitness landscape" defines the environment where organisms "live" or a problem that they are tested against. The landscape is intimately tied to the nature of the organism; think of an organism as a potential solution to a problem implemented by the landscape. A floating-point organism, for example, could be tested by a fitness landscape that represents a function to be maximized. Or, an organism describing the shape of wing could be tested by a landscape that simulates a wind tunnel.
Evocosms
The evocosm class binds a population of organisms to a set of objects that define the rules of survival and reproduction. An evocosm will have one or more populations, which will evolve against population-unique and shared (common) fitness landscapes; breeding is controlled by a set of class objects from the following classes.
Fitness Scaling
As a population converges on an "answer", the difference between fitness values often becomes very small; this prevents the best solutions from having a significant advantage in reproduction. Fitness scaling solves this problem by adjusting the fitness values to the advantage of the most-fit chromosomes. Evocosm includes a variety of fitness scaling algorithms.
Migration
A migrator removes individuals (via "emigration") from a population of organisms, transferring them to another population (via "immigration"). The only concrete implementation of this interface is random_pool_migrator, which defines a specific number of organisms that may migrate from each population to another. When creating a random_pool_migrator, specify the number of organisms that can migrate from each population. Migration is, of course, meaningless in any application that has only one population.
Selecting Survivors
A selector decides which organisms survive from one generation to the next. Some evolutionary algorithms will not use a selector; other will. In general, it is effective to keep the "best" organisms from one generation to the next, so that good genes do not become lost at random. This is, of course, an improvement on nature, where being "the best" doesnt guarantee survival.
Reproduction
In most cases, a reproducer generates new organisms using parents selected (by fitness) from an existing population. In some singular (and probably rare) cases, a reproducer might generate new, random organisms in order to keep diversity high. Reproduction techniques can include crossover and asexual, sexual and (my favorite) try-sexual models.
Mutation Operators
A mutator applies mutations (random, usually small changes) to a set of organisms. Mutation is highly dependent on the type of organism. In traditional genetic algorithms, a mutation flips one or more bits in an integer (i.e., chromosome). Evolving a path for the Traveling Salesman Problem involves complex mutations that maintain valid permutations of destination points; in the case of floating-point numbers, Ive provided utilities for mutating and crossing IEC-60559 (IEEE- 754) float and double types.
Enhancements:
- Minor bugfixes, code cleanups, and changes to pseudo-random number generators.
- Now includes Visual Studio 2005 projects along with GNU build files.
<<lessEvocosm is a set of classes that abstract the fundamental components of an evolutionary algorithm. Ill list the components here with a bit of introduction; you can review the details of the classes by downloading the code archives or by reviewing the online documentation (see the menu at the articles beginning for code and documentation links.)
All class documentation was generated from source code comments using doxygen. These docs have not been thoroughly proofread, so they may contain a few typos and minor errors. Self-publishing has taught me the value of a good proofreader.
Evolutionary algorithms come in a variety of shapes and flavors, but at their core, they all share certain characteristics: populations that reproduce and mutate through a series of generations, producing future generations based on some measure of fitness. An amazing variety of algorithms can be built on that general framework, which leads me to construct a set of core classes as the basis for future applications.
The classes include:
Random Numbers
Evocosm relies on the code in The Twisted Road to to Randomness for random number generation. The Mersenne Twister algorithm is particularly well-suited to evolutionary algorithms, based on its long period, granularity, "randomness", and speed. As of the 2.1.0 release of libevocosm, the mtprng class resides in libcoyote, and not libevocosm as it did earlier. This means that any program using libevocosm must also link against libcoyote.
Validation
To validate function arguments, Evocosm uses the code I describe in Beyond Assert; this code is part of libcoyote. Any program using libevocosm must also link against libcoyote.
Floating- Point Chromosomes
Evcosom supports the crossover and mutation of IEEE-754 floating-point numbers, using an algorithm I invented in the mid-1990s. This topic is covered in detail here.
Roulette Wheels
The roulette_wheel class implements the concept of a "software roulette wheel" for Evocosm. This is a tool for natural selection, wherein the fitness of an organism determines the width of its "slot" on an imaginary roulette wheel.
Organisms
Think of an "organism" as an answer to a problem posed by a fitness landscape; "genes" define its behavior and an associated fitness value is assigned by an evocosm during testing. Evocosm provides the freedom to define organisms as almost anything: bit strings, floating-point numbers, finite state machines, LISP programs, or external robots controlled via radio waves. In A Complexity of Options, I used an Evocosm-derived GA to determine the gcc options that produce the faster code.
Fitness Landscapes
A "fitness landscape" defines the environment where organisms "live" or a problem that they are tested against. The landscape is intimately tied to the nature of the organism; think of an organism as a potential solution to a problem implemented by the landscape. A floating-point organism, for example, could be tested by a fitness landscape that represents a function to be maximized. Or, an organism describing the shape of wing could be tested by a landscape that simulates a wind tunnel.
Evocosms
The evocosm class binds a population of organisms to a set of objects that define the rules of survival and reproduction. An evocosm will have one or more populations, which will evolve against population-unique and shared (common) fitness landscapes; breeding is controlled by a set of class objects from the following classes.
Fitness Scaling
As a population converges on an "answer", the difference between fitness values often becomes very small; this prevents the best solutions from having a significant advantage in reproduction. Fitness scaling solves this problem by adjusting the fitness values to the advantage of the most-fit chromosomes. Evocosm includes a variety of fitness scaling algorithms.
Migration
A migrator removes individuals (via "emigration") from a population of organisms, transferring them to another population (via "immigration"). The only concrete implementation of this interface is random_pool_migrator, which defines a specific number of organisms that may migrate from each population to another. When creating a random_pool_migrator, specify the number of organisms that can migrate from each population. Migration is, of course, meaningless in any application that has only one population.
Selecting Survivors
A selector decides which organisms survive from one generation to the next. Some evolutionary algorithms will not use a selector; other will. In general, it is effective to keep the "best" organisms from one generation to the next, so that good genes do not become lost at random. This is, of course, an improvement on nature, where being "the best" doesnt guarantee survival.
Reproduction
In most cases, a reproducer generates new organisms using parents selected (by fitness) from an existing population. In some singular (and probably rare) cases, a reproducer might generate new, random organisms in order to keep diversity high. Reproduction techniques can include crossover and asexual, sexual and (my favorite) try-sexual models.
Mutation Operators
A mutator applies mutations (random, usually small changes) to a set of organisms. Mutation is highly dependent on the type of organism. In traditional genetic algorithms, a mutation flips one or more bits in an integer (i.e., chromosome). Evolving a path for the Traveling Salesman Problem involves complex mutations that maintain valid permutations of destination points; in the case of floating-point numbers, Ive provided utilities for mutating and crossing IEC-60559 (IEEE- 754) float and double types.
Enhancements:
- Minor bugfixes, code cleanups, and changes to pseudo-random number generators.
- Now includes Visual Studio 2005 projects along with GNU build files.
Download (0.34MB)
Added: 2006-09-13 License: GPL (GNU General Public License) Price:
1138 downloads
Optimization Algorithm Toolkit 1.3
Optimization Algorithm Toolkit is a workbench and toolkit for developing, evaluating, and playing with optimization algorithms. more>>
Optimization Algorithm Toolkit is a workbench and toolkit for developing, evaluating, and playing with classical and state-of-the-art optimization algorithms on standard benchmark problem domains; including reference algorithm implementations, graphing, visualizations and much more. The project was developed initially by Jason Brownlee as a part of his Ph.D. program.
The goal of this project is to deliver obscure-and-prevalent, old-and-new optimization algorithms from research literature to both research scientists and algorithm practitioners alike. Algorithms include biologically inspired approaches such as evolutionary algorithms (genetic algorithms), swarm algorithms (ants and particle swarm), and immune system algorithms.
Also included are more conventional approaches such as approaches inspired by physics including simulated annealing and extremal optimization. Problem domains include numerical function optimization, traveling salesman problems, and protein folding all with many standard benchmark instances taken from research literature.
A user-friendly graphical interface is provided to rapidly evaluate and compare algorithm and problem configurations, visualize algorithm behavior, and graph algorithm performance over time. A robust, modular, and extensible framework underlies the platform to facilitate the easy addition and modification of algorithms, addition of new problem domains and problem instances as well as facilitate more advanced algorithm experimentation.
The algorithm implementations are extensible and easily support modification and applicaition to varied problem domains. Please report any bugs, feature requests or include your own algorithms by accessing the services on the project home website. This is an open source project (released under the GPL) so the source code is available. The project was compiled with Java 1.5 (update 9).
Enhancements:
- This release includes many framework and graphical interface fixes, as well as a few new algorithms to play with.
<<lessThe goal of this project is to deliver obscure-and-prevalent, old-and-new optimization algorithms from research literature to both research scientists and algorithm practitioners alike. Algorithms include biologically inspired approaches such as evolutionary algorithms (genetic algorithms), swarm algorithms (ants and particle swarm), and immune system algorithms.
Also included are more conventional approaches such as approaches inspired by physics including simulated annealing and extremal optimization. Problem domains include numerical function optimization, traveling salesman problems, and protein folding all with many standard benchmark instances taken from research literature.
A user-friendly graphical interface is provided to rapidly evaluate and compare algorithm and problem configurations, visualize algorithm behavior, and graph algorithm performance over time. A robust, modular, and extensible framework underlies the platform to facilitate the easy addition and modification of algorithms, addition of new problem domains and problem instances as well as facilitate more advanced algorithm experimentation.
The algorithm implementations are extensible and easily support modification and applicaition to varied problem domains. Please report any bugs, feature requests or include your own algorithms by accessing the services on the project home website. This is an open source project (released under the GPL) so the source code is available. The project was compiled with Java 1.5 (update 9).
Enhancements:
- This release includes many framework and graphical interface fixes, as well as a few new algorithms to play with.
Download (6.5MB)
Added: 2007-07-14 License: GPL (GNU General Public License) Price:
843 downloads
Minas 1.0
Minas provides a Java application which simulates bridge construction. more>>
Minas provides a Java application which simulates bridge construction.
Minas is a bridge simulation program. The name is actually Sindarin for "tower". Thats because the codebase originally came from a program that evolutionary creates towers and builds them higher and higher. After the towers were high enough, i took the code and made this game from it.
The gameplay, usage and rules is explained there. Please make use of the feature to send snapshots to the server.
minas.jar:
This file contains the source code and the compiled class files of minas. I apologize for the lack of documentation, but (as often) this project was only an experiment at the beginning, so i never started to document it.
You need a Java compiler to build it, and the Java Runtime Environment to run it.
<<lessMinas is a bridge simulation program. The name is actually Sindarin for "tower". Thats because the codebase originally came from a program that evolutionary creates towers and builds them higher and higher. After the towers were high enough, i took the code and made this game from it.
The gameplay, usage and rules is explained there. Please make use of the feature to send snapshots to the server.
minas.jar:
This file contains the source code and the compiled class files of minas. I apologize for the lack of documentation, but (as often) this project was only an experiment at the beginning, so i never started to document it.
You need a Java compiler to build it, and the Java Runtime Environment to run it.
Download (0.076MB)
Added: 2007-03-12 License: GPL (GNU General Public License) Price:
956 downloads
Coursor 1.0
Coursor project is a Web application for academic environments. more>>
Coursor project is a Web application for academic environments.
Coursor is a Web-based academic course system for assigning students to university courses.
It has an evolutionary algorithm for assigning students to the courses they requested. This algorithm tries to find an optimal distribution of students to existing courses while taking their preferences into account.
The system supports multiple roles for users: Admin, Student, Teacher/Prof, or Tutor.
A user can also have multiple roles.
It supports international localization, currently in English, German, French, Russian, and Arabic
Main features:
- Browser independent usage for students, teachers and admins alike (no frames, no necessary JavaScript, no cookies).
- Platform independent (entirely written in JAVA).
- Runs on APACHE Tomcat and uses a Postgresql Database.
- Evolutionary Algorithm to assign students to courses.
- Multiple Roles: Administrator, Teacher/Prof, Tutor and Student. One person can have multiple roles.
Enhancements:
- Encoding for Russian fixed
- PropertyEditor (propEdit.sf.net) programmed, will be released as own package. Eases Tranlation a lot.
- I18N target in build.xml starts PropertyEditor
- Serializable classes with ID (Eclipse wanted that)
<<lessCoursor is a Web-based academic course system for assigning students to university courses.
It has an evolutionary algorithm for assigning students to the courses they requested. This algorithm tries to find an optimal distribution of students to existing courses while taking their preferences into account.
The system supports multiple roles for users: Admin, Student, Teacher/Prof, or Tutor.
A user can also have multiple roles.
It supports international localization, currently in English, German, French, Russian, and Arabic
Main features:
- Browser independent usage for students, teachers and admins alike (no frames, no necessary JavaScript, no cookies).
- Platform independent (entirely written in JAVA).
- Runs on APACHE Tomcat and uses a Postgresql Database.
- Evolutionary Algorithm to assign students to courses.
- Multiple Roles: Administrator, Teacher/Prof, Tutor and Student. One person can have multiple roles.
Enhancements:
- Encoding for Russian fixed
- PropertyEditor (propEdit.sf.net) programmed, will be released as own package. Eases Tranlation a lot.
- I18N target in build.xml starts PropertyEditor
- Serializable classes with ID (Eclipse wanted that)
Download (1.5MB)
Added: 2006-10-19 License: GPL (GNU General Public License) Price:
1105 downloads
Bio::NEXUS 0.66
Bio::NEXUS is a Perl module providing an object-oriented, Perl-based applications programming interface (API). more>>
Bio::NEXUS is a Perl module providing an object-oriented, Perl-based applications programming interface (API).
NEXUS is a powerful and extensible format designed for use in evolutionary analysis, including the analysis of molecular sequence data as well as classical morphological and life-history data. It is the input or output format for software such as PAUP*, MacClade, Mesquite, SIMMAP, MrBayes, Nexplorer, and so on. This package also contains the demonstration applications nexplot.pl (plot character data with a tree) and nextool.pl (allowing programmatic editing, e.g., selecting particular clades or subsets of data).
The NEXPL library of Perl software (copyright 2004 Liang, Qiu and Yang) is distributed under an open source license (see LICENSE). If you use this software, please acknowledge:
Bio::NEXUS. An Object-oriented NEXUS API in Perl. T.J. Hladish, C.L. Liang, W.-G. Qiu, P. Yang, V. Gopalan and A. Stoltzfus. Available at http://www.molevol.org/camel/software.
INSTALLATION AND TESTING
This software has been tested under Linux as well as MaxOS X 10.2 and higher, and even a few Windows installations. The package installs using the standard procedure, and runs several hundred tests:
perl Makefile.PL
make
make test
make install
For more information, or to customize, see doc/Installation.pod.
<<lessNEXUS is a powerful and extensible format designed for use in evolutionary analysis, including the analysis of molecular sequence data as well as classical morphological and life-history data. It is the input or output format for software such as PAUP*, MacClade, Mesquite, SIMMAP, MrBayes, Nexplorer, and so on. This package also contains the demonstration applications nexplot.pl (plot character data with a tree) and nextool.pl (allowing programmatic editing, e.g., selecting particular clades or subsets of data).
The NEXPL library of Perl software (copyright 2004 Liang, Qiu and Yang) is distributed under an open source license (see LICENSE). If you use this software, please acknowledge:
Bio::NEXUS. An Object-oriented NEXUS API in Perl. T.J. Hladish, C.L. Liang, W.-G. Qiu, P. Yang, V. Gopalan and A. Stoltzfus. Available at http://www.molevol.org/camel/software.
INSTALLATION AND TESTING
This software has been tested under Linux as well as MaxOS X 10.2 and higher, and even a few Windows installations. The package installs using the standard procedure, and runs several hundred tests:
perl Makefile.PL
make
make test
make install
For more information, or to customize, see doc/Installation.pod.
Download (0.15MB)
Added: 2006-09-06 License: Perl Artistic License Price:
1143 downloads
Open BEAGLE 3.0.1
Open BEAGLE is an evolutionary computation framework in C++. more>>
Open BEAGLE is a C++ Evolutionary Computation (EC) framework. It provides an high-level software environment to do any kind of EC, with support for tree-based genetic programming, bit string and real-valued genetic algorithms, and evolution strategy.
The Open BEAGLE architecture follows strong principles of object oriented programming, where abstractions are represented by loosely coupled objects and where it is common and easy to reuse code.
Open BEAGLE is designed to provide an EC environment that is generic, user friendly, portable, efficient, robust, elegant and free.
With Open BEAGLE, the user can execute any kind of EC, as far as it fulfills some minimum requirements. The only necessary condition is to have a population of individuals to which a sequence of evolving operations is iteratively applied.
So far, Open BEAGLE supports most mainstream EC flavors such genetic programming, bit string and real-values genetic algorithms, and evolution strategy. It also includes support for advanced EC techniques such multiobjective optimization and co-evolution.
The user can take any of these specialized frameworks and modify them further to create his own specialized flavor of evolutionary algorithms.
Main features:
User Friendliness
- Considerable efforts were deployed to make the use of Open BEAGLE as easy and pleasant as possible. Open BEAGLE possesses several mechanisms that offer a user friendly programming interface. For example, the memory management of dynamically allocated objects is greatly simplified by the use of reference counting and automatic garbage collection. The programming style promoted is high-level and allows rapid prototyping of applications.
Portability
- The Open BEAGLE code is compliant with the C++ ANSI/ISO 3 standard. It requires the Standard Template Library (STL). No specific call in the core libraries are made to the operating system nor to the hardware.
Efficiency
- To insure efficient execution, particular attention was given to optimization of critical code sections. Detailed execution profiles of these sections were done. Also, the fact that Open BEAGLE is written in C++ contributes to its overall good performance.
Robustness
- Many verification and validation statements are embedded into the code to ensure correct operation and to inform the user when there is a problem. Robust mechanisms for periodically saving the current evolution state have also been implemented in order to enable automatic restart of interrupted evolutions.
Elegance
- The interface of Open BEAGLE was developed with care. Great energy was invested in designing a coherent software package that follows good OO and generic programming principles. Moreover, strict programming rules were enforced to make the C++ code easy to read, understand and, eventually, modify. The use of XML as file format is also a central aspect of Open BEAGLE, which provide a common ground for tools development to analyze and generate files, and to integrate the framework with other systems.
Free Sourceness
- The source code of Open BEAGLE is free, available under the GNU Lesser General Public License (LGPL). Thus, it can be distributed and modified without any fee. (See section copyright for further details.
Enhancements:
- Several fixes to allow compilation on Mac OS X
- Fixes in headers inclusion to allow precompiled headers
<<lessThe Open BEAGLE architecture follows strong principles of object oriented programming, where abstractions are represented by loosely coupled objects and where it is common and easy to reuse code.
Open BEAGLE is designed to provide an EC environment that is generic, user friendly, portable, efficient, robust, elegant and free.
With Open BEAGLE, the user can execute any kind of EC, as far as it fulfills some minimum requirements. The only necessary condition is to have a population of individuals to which a sequence of evolving operations is iteratively applied.
So far, Open BEAGLE supports most mainstream EC flavors such genetic programming, bit string and real-values genetic algorithms, and evolution strategy. It also includes support for advanced EC techniques such multiobjective optimization and co-evolution.
The user can take any of these specialized frameworks and modify them further to create his own specialized flavor of evolutionary algorithms.
Main features:
User Friendliness
- Considerable efforts were deployed to make the use of Open BEAGLE as easy and pleasant as possible. Open BEAGLE possesses several mechanisms that offer a user friendly programming interface. For example, the memory management of dynamically allocated objects is greatly simplified by the use of reference counting and automatic garbage collection. The programming style promoted is high-level and allows rapid prototyping of applications.
Portability
- The Open BEAGLE code is compliant with the C++ ANSI/ISO 3 standard. It requires the Standard Template Library (STL). No specific call in the core libraries are made to the operating system nor to the hardware.
Efficiency
- To insure efficient execution, particular attention was given to optimization of critical code sections. Detailed execution profiles of these sections were done. Also, the fact that Open BEAGLE is written in C++ contributes to its overall good performance.
Robustness
- Many verification and validation statements are embedded into the code to ensure correct operation and to inform the user when there is a problem. Robust mechanisms for periodically saving the current evolution state have also been implemented in order to enable automatic restart of interrupted evolutions.
Elegance
- The interface of Open BEAGLE was developed with care. Great energy was invested in designing a coherent software package that follows good OO and generic programming principles. Moreover, strict programming rules were enforced to make the C++ code easy to read, understand and, eventually, modify. The use of XML as file format is also a central aspect of Open BEAGLE, which provide a common ground for tools development to analyze and generate files, and to integrate the framework with other systems.
Free Sourceness
- The source code of Open BEAGLE is free, available under the GNU Lesser General Public License (LGPL). Thus, it can be distributed and modified without any fee. (See section copyright for further details.
Enhancements:
- Several fixes to allow compilation on Mac OS X
- Fixes in headers inclusion to allow precompiled headers
Download (4.7MB)
Added: 2005-10-10 License: LGPL (GNU Lesser General Public License) Price:
1477 downloads
OneBone Puppy 2.00r1
Puppy Linux is an evolutionary operating system, based on GNU Linux. more>>
This is a play-thing, requested by a few people on the forum, and definitely not for the average user. In other words, Linux commandline nerds only! OneBone does not have any X GUI applications.
It does have Elinks web browser, Ytree file manager and MP text editor. The Lucent and SmartLink modem drivers are included. There are lots of text-mode applications out there and a very interesting flavour of Puppy could be created, based on this starting point.
Puppy Linux is an evolutionary operating system, based on GNU Linux. Whats different here is that Puppy is extraordinarily small, yet quite full featured. Puppy Linux can boot into a 64MB ramdisk, and thats it, the whole caboodle runs in RAM.
Unlike live CD distributions that have to keep pulling stuff off the CD, Puppy in its entirety loads into RAM. This means that all applications start in the blink of an eye and respond to user input instantly.
Puppy Linux has the ability to boot off a flash card or any USB memory device (flash-Puppy), CDROM (live-Puppy), Zip disk or LS/120/240 Superdisk (zippy-Puppy), floppy disks (floppy-Puppy), internal hard drive (hard-Puppy).
<<lessIt does have Elinks web browser, Ytree file manager and MP text editor. The Lucent and SmartLink modem drivers are included. There are lots of text-mode applications out there and a very interesting flavour of Puppy could be created, based on this starting point.
Puppy Linux is an evolutionary operating system, based on GNU Linux. Whats different here is that Puppy is extraordinarily small, yet quite full featured. Puppy Linux can boot into a 64MB ramdisk, and thats it, the whole caboodle runs in RAM.
Unlike live CD distributions that have to keep pulling stuff off the CD, Puppy in its entirety loads into RAM. This means that all applications start in the blink of an eye and respond to user input instantly.
Puppy Linux has the ability to boot off a flash card or any USB memory device (flash-Puppy), CDROM (live-Puppy), Zip disk or LS/120/240 Superdisk (zippy-Puppy), floppy disks (floppy-Puppy), internal hard drive (hard-Puppy).
Download (26.4MB)
Added: 2006-06-12 License: GPL (GNU General Public License) Price:
1234 downloads
Ventrilo Server 2.3.1
Ventrilo is the next evolutionary step of Voice over IP (VoIP) group communications software. more>>
Ventrilo is the next evolutionary step of Voice over IP (VoIP) group communications software. Ventrilo is also the industry standard by which all others measure them selves as they attempt to imitate its features.
By offering surround sound positioning and special sound effects on a per user, per channel, per server or global configuration level the program provides each user the option to fully customize exactly how they wish to hear sounds from other users or events.
Ventrilo is best known for its superior sound quality and minimal use of CPU resources so as not to interfere with day to day operations of the computer or during online game competitions. It is also preferred for the simple user interface that any first time computer user can very quickly learn because the most commonly used features are immediately visible and can be activated with a single click of the mouse.
<<lessBy offering surround sound positioning and special sound effects on a per user, per channel, per server or global configuration level the program provides each user the option to fully customize exactly how they wish to hear sounds from other users or events.
Ventrilo is best known for its superior sound quality and minimal use of CPU resources so as not to interfere with day to day operations of the computer or during online game competitions. It is also preferred for the simple user interface that any first time computer user can very quickly learn because the most commonly used features are immediately visible and can be activated with a single click of the mouse.
Download (0.16MB)
Added: 2005-11-17 License: Freeware Price:
2164 downloads
EASEA 0.7b
EASEA project is a language dedicated to the specification of evolutionary algorithms. more>>
EASEA project is a language dedicated to the specification of evolutionary algorithms.
EAsea Specification of Evolutionary Algorithms (EASEA), is a high-level language dedicated to the specification of evolutionary algorithms.
The language and compiler are quite mature. EASEA compiles .ez specification files into C++ or Java object files, using existing evolutionary libraries. Supported C++ libraries currently are GALib or EO.
Enhancements:
- EASEA now features a Graphic User Interface for the Description of Experiment (GUIDE) which is in its 0.1 version (meaning it is still quite young and probably not bug-free).
- As far as EASEA is concerned, this 0.7b version does not yet handle GALib.
- Many parameters were added to pilot the quite complete EO library, and this version can be used to create JEO java experiments for the DREAM.
<<lessEAsea Specification of Evolutionary Algorithms (EASEA), is a high-level language dedicated to the specification of evolutionary algorithms.
The language and compiler are quite mature. EASEA compiles .ez specification files into C++ or Java object files, using existing evolutionary libraries. Supported C++ libraries currently are GALib or EO.
Enhancements:
- EASEA now features a Graphic User Interface for the Description of Experiment (GUIDE) which is in its 0.1 version (meaning it is still quite young and probably not bug-free).
- As far as EASEA is concerned, this 0.7b version does not yet handle GALib.
- Many parameters were added to pilot the quite complete EO library, and this version can be used to create JEO java experiments for the DREAM.
Download (0.31MB)
Added: 2006-11-01 License: GPL (GNU General Public License) Price:
1088 downloads
Grammidity 1.0
Grammidity project is a Java-based framework for evolutionary programming. more>>
Grammidity project is a Java-based framework for evolutionary programming.
It can be used to evolve solutions to problems, or to evolve "objects" under user control.
It has a limitless range of possible applications.
This program has been tested on sample projects generating 3D objects and imitation plants.
<<lessIt can be used to evolve solutions to problems, or to evolve "objects" under user control.
It has a limitless range of possible applications.
This program has been tested on sample projects generating 3D objects and imitation plants.
Download (0.81MB)
Added: 2006-10-12 License: GPL (GNU General Public License) Price:
1109 downloads
Distributed BEAGLE 0.9.2
Distributed BEAGLE provides a distributed evolutionary computation system. more>>
Distributed BEAGLE provides a distributed evolutionary computation system.
Distributed BEAGLE is a master-slave distribution extension of the evolutionary computation framework, Open BEAGLE. Its key features are robustness, fault tolerance, adaptability for heterogeneous networks, and transparency for the user.
Main features:
- Based on the generic framework Open BEAGLE
- Minimal changes required to modify an Open BEAGLE application for distribution
- Ten GA and GP examples converted from Open BEAGLE
- Communication based on TCP sockets using XML encoding
- Data persistency insured on the server by a SQL Database (SQLite)
- Load balancing of computational tasks for uses on heterogeneous LAN
- Open source (LGPL license)
- OS-calls wrapped into generic C++ classes
- Compiles on UNIX (Linux/OS X) with gcc 3.x and Windows with Visual Studio .NET
Enhancements:
- Bug fixe: variable deme size could crash the server (Thanks CG).
- Suggestion: Compression of connections can now be activated by clients if the option is set to "-1".
<<lessDistributed BEAGLE is a master-slave distribution extension of the evolutionary computation framework, Open BEAGLE. Its key features are robustness, fault tolerance, adaptability for heterogeneous networks, and transparency for the user.
Main features:
- Based on the generic framework Open BEAGLE
- Minimal changes required to modify an Open BEAGLE application for distribution
- Ten GA and GP examples converted from Open BEAGLE
- Communication based on TCP sockets using XML encoding
- Data persistency insured on the server by a SQL Database (SQLite)
- Load balancing of computational tasks for uses on heterogeneous LAN
- Open source (LGPL license)
- OS-calls wrapped into generic C++ classes
- Compiles on UNIX (Linux/OS X) with gcc 3.x and Windows with Visual Studio .NET
Enhancements:
- Bug fixe: variable deme size could crash the server (Thanks CG).
- Suggestion: Compression of connections can now be activated by clients if the option is set to "-1".
Download (MB)
Added: 2007-03-21 License: LGPL (GNU Lesser General Public License) Price:
948 downloads
Blogfish 1.0
Blogfish is the memepool. more>>
Blogfish is the memepool.
Blogfish is social networking meets evolutionary software meets peer-to-pier networking. Blogfish is best eaten wrapped in newspaper, with salt and vinegar. Blogfish is the fin end of the wedge.
More prosaically, blogfish is a Gnome panel applet, written in Python using PyGTK and Gnome-python. It allows you to spread your blog URL, website URL or random thoughts to other users. Good memes survive; bad ones are voted down and go belly up.
Main features:
- New simple peer for running on servers, systems without X
- RPM!
- Bugfixes: no longer sucks so much memory; dies nicely on exit; networking bugs, lots; resizes nicely
- Drag and drop URL to add new fish
- Nice new icon
- UI compatibility with the HIG
- Simpler install script
- Compatibility with Python < 2.3
- Beaten to release by Sarge, FFS
<<lessBlogfish is social networking meets evolutionary software meets peer-to-pier networking. Blogfish is best eaten wrapped in newspaper, with salt and vinegar. Blogfish is the fin end of the wedge.
More prosaically, blogfish is a Gnome panel applet, written in Python using PyGTK and Gnome-python. It allows you to spread your blog URL, website URL or random thoughts to other users. Good memes survive; bad ones are voted down and go belly up.
Main features:
- New simple peer for running on servers, systems without X
- RPM!
- Bugfixes: no longer sucks so much memory; dies nicely on exit; networking bugs, lots; resizes nicely
- Drag and drop URL to add new fish
- Nice new icon
- UI compatibility with the HIG
- Simpler install script
- Compatibility with Python < 2.3
- Beaten to release by Sarge, FFS
Download (0.14MB)
Added: 2005-07-22 License: GPL (GNU General Public License) Price:
1554 downloads
Neurofitter 0.9.2
A software for parameter tuning of electrophysiological neuron model. more>> Neurofitter is software for parameter tuning of electrophysiological neuron models.
It automatically searches for sets of parameters of neuron models that best fit available experimental data, and therefore acts as an interface between neuron simulators, like Neuron or Genesis, and optimization algorithms, like Particle Swarm Optimization, Evolutionary Strategies, etc.
.<<less
Download (225KB)
Added: 2009-04-07 License: Others Price: FREE
199 downloads
Puppy Linux 4.2.1
Puppy Linux provides you with a perfect and very useful evolutionary operating system which is based on GNU Linux. more>>
Puppy Linux 4.2.1 provides you with a perfect and very useful evolutionary operating system which is based on GNU Linux. Whats different here is that Puppy is extraordinarily small, yet quite full featured. Puppy Linux can boot into a 64MB ramdisk, and that's it, the whole caboodle runs in RAM. Unlike live CD distributions that have to keep pulling stuff off the CD, Puppy in its entirety loads into RAM. This means that all applications start in the blink of an eye and respond to user input instantly.
Major Features:
- Puppy Linux has the ability to boot off a flash card or any USB memory device (flash-Puppy), CDROM (live-Puppy), Zip disk or LS/120/240 Superdisk (zippy-Puppy), floppy disks (floppy-Puppy), internal hard drive (hard-Puppy).
- Puppy occupies about 50-60M on my USB Flash drive, CDROM, or whatever is the storage media.
- When Puppy boots, everything uncompressed into a RAM area that we call a "ramdisk". The live-CD will bootup on systems with only 32M RAM, but the more RAM you have the more Puppy is able to keep files permanently in ramdisk hence more speed. A PC with 128M RAM is the recommended minimum.
- Note that Puppy will automatically use a swap partition if it exists. When booting from a USB Flash device, Puppy tries to load all the Flash files into physical RAM, but if there is not enough RAM then Puppy is able to copy the excess to a swap partition if it exists. This eliminates writes to the Flash memory during a session, greatly extending its life span.
- You may need to have a swap partition to run Firefox or Mozilla on PCs with less than 64M RAM. Certainly, for a PC with only 32M RAM, a swap partition is necessary to run most of the large GUI applications.
Enhancements:
- CUPS-1.3.10 regressed from 1.4b2 to resolve ongoing issues with CUPS printing.
- Fixed printing from Geany, Leafpad and Gnumeric using CUPS-1.3.10
- Abiword-2.6.3 with 2.6.6 plugins has been patched for improved .doc & .docx support (Liberation ttf fonts required for some documents)
- Pwidgets updated to 2.0.8
- Pcrypt updated to 17 May 2009 release and now requires Ccrypt to function. Bcrypt has been dropped in consequence.
- Ccrypt-1.7 added as dependency for Pcrypt
- MIME-types updated in Rox-2.6.1
- Patches for gtk+ Xinput and b43 broadcom network driver
- Pmusic updated to 0.6.4
- Pschedule updated to 0.7
- Plus previously issued patches for nbtscan, mountcifs, jwm-tray, xsane, network wizard (now at April 4 release), mtpaint-snapshot, gtk+2.12.1-Xinput-fix and pcp (Puppy control panel).
Added: 2009-05-22 License: GPL Price: FREE
1 downloads
Other version of Puppy Linux
Barry Kauler - Puppy Linux is an evolutionary operating system, based on GNU Linux. Puppy Linux. Puppy Linux is an evolutionary operatingLicense:GPL (GNU General Public License)
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