Search Results for "8-puzzle reinforcement learning python" - Page 3

Showing 66 open source projects for "8-puzzle reinforcement learning python"

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  • 1
    Exposure

    Exposure

    Learning infinite-resolution image processing with GAN and RL

    Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model. ACM Transactions on Graphics (presented at SIGGRAPH 2018) Exposure is originally designed for RAW photos, which assumes 12+ bit color depth and linear "RGB" color space (or whatever we get after demosaicing). jpg and png images typically have only 8-bit color depth (except 16-bit pngs) and the lack of information (dynamic range/activation resolution) may lead...
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  • 2
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu backend...
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  • 3
    WikiSQL

    WikiSQL

    A large annotated semantic parsing corpus for developing NL interfaces

    A large crowd-sourced dataset for developing natural language interfaces for relational databases. WikiSQL is the dataset released along with our work Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning. Regarding tokenization and Stanza, when WikiSQL was written 3-years ago, it relied on Stanza, a CoreNLP python wrapper that has since been deprecated. If you'd still like to use the tokenizer, please use the docker image. We do not anticipate switching...
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  • 4
    Super Kanji Time II

    Super Kanji Time II

    A time attack game for learning various kanji.

    This is a game developed in Python and compiled for Windows XP, Vista, 7, and 8 that is built to teach various kanji to students of the Japanese language. The kanji lists are taken from the textbook Nakama 2. In this game, you must click on the appropriate kanji according to the pronunciation given to you. When a correct click is made, a sound plays and the kanji disappears. The goal is to make all the kanji disappear as fast as you can. You can compete against yourself, classmates...
    Downloads: 0 This Week
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  • 5
    Super Kanji Time I

    Super Kanji Time I

    A time attack game for learning various kanji.

    This is a game developed in Python and compiled for Windows XP, Vista, 7, and 8 that is built to teach various kanji to students of the Japanese language. The kanji lists are taken from the textbook Nakama 2. In this game, you must click on the appropriate kanji according to the pronunciation given to you. When a correct click is made, a sound plays and the kanji disappears. The goal is to make all the kanji disappear as fast as you can. You can compete against yourself, classmates...
    Downloads: 0 This Week
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  • 6
    Kana Attack III

    Kana Attack III

    A time attack game for learning hiragana and katakana.

    This is a game developed in Python and compiled for Windows XP, Vista, 7, and 8 that is built to teach the kana syllabaries to students of the Japanese language. In this game, you must click on the appropriate hiragana or katakana symbol according to the pronunciation given to you. When a correct click is made, a sound plays and the kana disappears. The goal is to make all the kana disappear as fast as you can. You can compete against yourself, classmates, or friends using a local...
    Downloads: 0 This Week
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  • 7

    iget

    Adaptive Parallel Data Retrieval Mechanism

    Adaptive Synchronous-Retrieval mechanism with Concurrent I/O using Reinforcement Learning. A data retrieval mechanism that can adapt to the continuous contraction and expansion of the network bottleneck so that an optimal concurrency index can be maintained at any time during the data retrieval process. Sample usage: python iget.py <target url> <output file>
    Downloads: 0 This Week
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  • 8
    This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.
    Downloads: 0 This Week
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  • 9
    In this Project, We solved 8-puzzle problem, very famous problem in AI, by using reinformcemnt learning concepts.
    Downloads: 0 This Week
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  • 10
    A Python class library of tools for learning agents, including reinforcement learning algorithms, function approximators, and vector quantizations algorithms. (Pronounced "plastic".)
    Downloads: 0 This Week
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  • 11
    A general purpose reinforcement learning engine.
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  • 12
    Match a picture with its name in the alloted time to win. This game is played like the game known as Concentration, Memory or Match. There are multiple levels, a highscore, and soundtrack. This game might be helpful to someone learning Python and pyGame
    Downloads: 1 This Week
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  • 13
    General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
    Downloads: 0 This Week
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  • 14
    PySet is an incremental implementation of the classic logic/card game Set, built using Python, Simple Direct-media Library (SDL), and PyGame (a Python wrapper of the SDL API). The code is intended to assist newcomers in gradually learning these libs.
    Downloads: 0 This Week
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  • 15
    A Python translation of Piqle with Traits for simplified simulation with reinforcement learning agents.
    Downloads: 0 This Week
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  • 16

    text_summurization_abstractive_methods

    Multiple implementations for abstractive text summurization

    This repo is built to collect multiple implementations for abstractive approaches to address text summarization it is built to simply run on google colab , in one notebook so you would only need an internet connection to run these examples without the need to have a powerful machine , so all the code examples would be in a jupyter format , and you don't have to download data to your device as we connect these jupyter notebooks to google drive
    Downloads: 0 This Week
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