Showing 138 open source projects for "linux ai"

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  • 1
    TGAN

    TGAN

    Generative adversarial training for generating synthetic tabular data

    We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid...
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  • 2
    Zhao

    Zhao

    A compilation of "The Princely Party Relationship Network"

    zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates...
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  • 3
    A software toolkit that implements the CoSy Architecture Schema for developing integrated intelligent robotic systems. The toolkit focuses on supporting on a space of information-processing architectures based on shared working memories.
    Downloads: 0 This Week
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  • 4
    Belkerda

    Belkerda

    a customizable number-guessing system

    Belkerda is a simple Python AI program that takes a user's input, builds a log of random numbers, picks a random entry, and displays it. If it is correct, then it reenters that number back into the log several times, overwriting the original, random numbers. If it is not, however, it overwrites a lower amount of entries.
    Downloads: 0 This Week
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  • 5
    Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
    Downloads: 0 This Week
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  • 6
    Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.
    Downloads: 1 This Week
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  • 7
    VRT is a Virtual Reality Toolkit. It is planned to be OS-independent, easy-to-use, full-feature VR platform. It integrates 3D engine, physical engine and AI engine.
    Downloads: 0 This Week
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  • 8
    The Mandragora World Engine is a C++/Python engine which allows the easy creation of programs, including applications, simulations, and games. Able to load and run specific program modules. Will handle objects, graphics, sound, physics, GUI, and even AI.
    Downloads: 0 This Week
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  • 9
    Sakura is a Knowledge Navigator and User Interface for UNIX, which implements HyperMedia and its own windowing and packing system, both in the main program and in an extensive API for Tcl and other languages.
    Downloads: 1 This Week
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  • 10
    A simple, yet powerful framework built around the OGRE rendering system. Has many features in the works such as AI, Audio, an entity system (much like CEL), and a complete level editor.
    Downloads: 0 This Week
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  • 11
    Educational game framework supporting board games, strategy games, and other grid-based game boards. Currently uses Python/wxPython as the application language/library. C++ libs included to help create AI for the various games.
    Downloads: 2 This Week
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  • 12
    FEAR is a development kit helping software engineers create advanced artificial intelligence in synthetic characters with simplicity and efficiency. The project includes reusable AI components, portable framework and interfaces to realtime 3D games.
    Downloads: 2 This Week
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  • 13
    Zeus Grid is a Grid Computing environment usefull to run systems in heterogenous machines at same time. In this first step, it will only compile, run and collect application results and file storage.
    Downloads: 0 This Week
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