Showing 6 open source projects for "monte carlo simulation"

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  • 1
    Reinforcement-learning

    Reinforcement-learning

    Implementation of Reinforcement Learning Algorithms. Python, OpenAI

    Reinforcement-learning is a widely used educational repository that provides implementations, exercises, and solutions for a broad range of reinforcement learning algorithms, designed to complement foundational texts and courses in the field. The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. ...
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  • 2
    Programmer's library for random numbers. Also random number generator testing code. Intended for simulation, games and "Monte-Carlo" algorithms.
    Downloads: 1 This Week
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  • 3
    Analytic Toolkit
    The purpose of the project is summarising effort from a number of analytic libraries, adding interactive web-based user interface and making a free open source solution for risk analytics and stress testing. Feb 8, 2012 Paul Glasserman's Importance Sampling and Tail Approximations as well as plain Monte Carlo have been implemented for for the widely used normal copula model of portfolio credit risk. The package includes source code, examples, spreadsheet with results and references to the papers.
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  • 4
    Tina's Random Number Generator Library (TRNG) is a state of the art C++ pseudo-random number generator library for sequential and parallel Monte Carlo simulations.
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  • 5
    The Tomographic Image Reconstruction Interface of the Universite de Sherbrooke (TIRIUS) is a Qt-based user-interface software for reconstructing 3D images from data generated by real apparatus or generated by the GATE Monte Carlo simulator.
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  • 6
    TAROT is a easy-to-use framework for Monte Carlo simulations in python. Calculations between different kinds of randomly distributed numbers are made as easy as basic arithmetics. Tarot provides an interactive graphical interface for interpretation.
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