Showing 4 open source projects for "q-learning"

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  • 1
    OSXtlearn

    OSXtlearn

    OSXtlearn: tlearn for MacOSX

    tlearn is a backpropagation neural network simulator, written by Jeff Elman. xtlearn is a version of tlearn for the X Window System. OSXtlearn is xtlearn wrapped in a MacOSX application bundle that runs ons MacOSX 10.5 or higher and that requires XQuartz. OSXtlearn is created by Harm Brouwer.
    Downloads: 0 This Week
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  • 2
    AHANNS

    AHANNS

    AHANNS - Amateur Homemade Artificial Neural Network Simulator

    AHANNS enables the user to create and train artificial neural networks. Training is carried out by an implementation of back propagation learning algorithm. See the documentation for details. This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful...
    Downloads: 0 This Week
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  • 3
    A network simulator written in flash. Build up a topolog and send packets throught your network, see and inspect them as they travel, change the headers and observe such protocols as ARP and switch learning.
    Downloads: 0 This Week
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  • 4
    GNNS - GNNS Neural Network Simulator, is both a set of libraries and an interface for creating and learning neural networks. It is aimed to support as many network typs and learning algorithms as possible. GNNS is meant to support different platforms.
    Downloads: 0 This Week
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  • Make Your Observability Stack Effortless Icon
    Make Your Observability Stack Effortless

    For Software Engineers, DevOps, Data Architects, and IT Leaders

    The progression to modern application stacks and microservices architectures has resulted in orders of magnitude more logs, metrics, events, and traces. Like gravity, data attracts more data, making it increasingly difficult to move and process as it accumulates over time. More than ever, there is a need to be able to stream-process, filter, mask, transform, aggregate, analyze, and route that data to various data tier destinations optimized for specific usage.
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