Search Results for "python q learning"
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Showing 17 open source projects for "python q learning"
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NVIDIA Isaac Lab
Unified framework for robot learning built on NVIDIA Isaac Sim
Isaac Lab is an open-source modular robotics learning framework built atop Isaac Sim. It simplifies research workflows across reinforcement learning, imitation learning, and motion planning by offering robust, GPU-accelerated simulation with realistic sensor and physics fidelity—ideal for sim-to-real robot training. Compatible and optimized for use with Isaac Sim versions (e.g., Sim 5.0 and 4.5). GPU-accelerated, high-fidelity physics and sensor simulation suitable for complex learning... -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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robosuite
A Modular Simulation Framework and Benchmark for Robot Learning
Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning. -
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Newton
An open-source, GPU-accelerated physics simulation engine
Newton is a high-performance, GPU-accelerated physics simulation engine designed primarily for robotics research, machine learning, and advanced simulation workflows. Built on top of NVIDIA Warp, it leverages GPU parallelism to deliver scalable and efficient simulation environments that support rapid iteration and experimentation. The engine extends previous simulation frameworks by introducing differentiable physics capabilities, allowing it to integrate seamlessly with machine learning... -
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FEATool Multiphysics - FEA & CFD Toolbox
FEATool Multiphysics is an easy-to-use FEA and CFD Simulation Toolbox
...In addition to built-in CAD and pre/post-processing, automatic mesh generation, and multi-physics solvers, FEATool also seamlessly integrates the state-of-the-art OpenFOAM [1], SU2, and FEniCS CFD and FEA solvers. Moreover, native itegration with MATLAB and Python allows advanced simulation scripts and programmatic use cases such as in AI and machine learning [2]. [1]: https://www.featool.com/Easy-to-Use-OpenFOAM-GUI/ [2]: https://featool.com/model-showcase/2024-11-12-CFD-and-Flow-Prediction-Based-on-Deep-Learning... -
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GNNPCSAFT
Smart Thermodynamic Modeling with Graph Neural Networks
The GNNPCSAFT app is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. To install the GNNPCSAFT app, download the... -
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GNNPCSAFT Web App
Smart Thermodynamic Modeling with Graph Neural Networks
The GNNPCSAFT Web App is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. More info on github repository. -
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Kinetic.jl
Universal modeling and simulation of fluid mechanics upon ML
Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs. -
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MuJoCo-py
mujoco-py allows using MuJoCo from Python 3
mujoco-py is a Python wrapper for MuJoCo, a high-performance physics engine widely used in robotics, reinforcement learning, and AI research. It allows developers and researchers to run detailed rigid body simulations with contacts directly from Python, making MuJoCo easier to integrate into machine learning workflows. The library is compatible with MuJoCo version 2.1 and supports Linux and macOS, while Windows support has been deprecated. -
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ModbusPal - a Java MODBUS simulator
Modbus slave simulator
ModbusPal is a project to develop a PC-based Modbus simulator. Its goal is to reproduce a realistic environment, with many slaves and animated register values. Almost everything in ModbusPal can be customized and controlled by scripts. -
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RoboSchool
Open source software for robot simulation, integrated with OpenAI Gym
Roboschool is a set of open source robot simulation environments for reinforcement learning, created as an alternative to the Mujoco physics engine. It integrates with OpenAI Gym and provides a variety of continuous control tasks, including humanoid locomotion, quadrupeds, and robotic arms. The library is built on the Bullet Physics engine, making it accessible without the licensing requirements of Mujoco. Roboschool includes training scripts and examples for applying reinforcement learning... -
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2D Structural Analysis
Determine the bending moments, shear forces, axial forces and displace
2D Structural Analysis in Python by Ritchie Vink A collection examples of 2D Finite Element Analysis (FEA) made with Jupyter Notebook Lab - https://jupyter.org/ To install Jupyter - https://jupyter.org/install ===== App is available on Play Store -> https://play.google.com/store/apps/details?id=com.ulm.struct If you want to download a python editor for your android smartphone follow this link -> https://play.google.com/store/apps/details?id=com.ulm.python -
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Virtual Botmaster
Simulate Botnet NetFlow traffic for research analysis
Simulate Botnet NetFlow traffic for research analysis -
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XNDiff
X-ray and Neutron powder pattern simulation analysis
Keywords (XNDiff): -SAXS -SANS -absolute units -core (double)shell crystalline nanoparticles -with a parallelepidal shape -particle assemblies -powder and ensemble average -C/C++ -Unix -OpenMP -HPC Cluster Keywords (BatchMultiFit): -simultaneous fits for several SAXS and SANS curves with simulation data from XNDiff -SANS data can be smeared with dq values from experimental data sets or analytical functions -Mathematica console -local and global optimizers (simulated annealing, differential evolution, Nelder-Mead, ...) can be used -range for fit parameters and further constraints between fit parameters -parallelized (typ. 4-8 threads) TODO (BatchMultiFit): -read and use errorbars from experimental data sets -allow different q-ranges for different data sets in the fits -rewrite and test in Python using e.g. the lmfit module: https://pypi.python.org/pypi/lmfit/ to get rid of Mathematica and to run it on HPC clusters -
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A base for programs. Includes algorythms for Q-learning and SOM's etc. too. Examples: Hamron: Simulates evolution, uses the 2D-renderer. DriveUnit: created for school, for a robotic arm, uses the 3D-renderer. Hlearn: http://www.sagenb.org/home/pub/8
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ppc_sim_booke
e500v2 simulator
An experimental ISS for freescale's e500v2 core. It is meant to simulate only cpu and memory subsystem and is purely intended for academic/learning purposes only. -
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