https://ramdi.fr/tags/reinforcement-learning/Recent content in Reinforcement-Learning on Noureddine RAMDIHugoenSat, 23 May 2026 20:41:27 +0000https://ramdi.fr/github-stars/exploring-gmr-real-time-cross-embodiment-human-motion-retargeting-for-humanoid-robots/Sat, 23 May 2026 20:41:14 +0000https://ramdi.fr/github-stars/exploring-gmr-real-time-cross-embodiment-human-motion-retargeting-for-humanoid-robots/GMR is a Python library that retargets human motion from multiple formats onto 17+ humanoid robots in real time on CPU, tuned for RL tracking policies and whole-body teleoperation.https://ramdi.fr/github-stars/graph-r1-reinforcement-learning-to-train-llms-for-reasoning-over-knowledge-graphs/Sat, 23 May 2026 20:41:14 +0000https://ramdi.fr/github-stars/graph-r1-reinforcement-learning-to-train-llms-for-reasoning-over-knowledge-graphs/Graph-R1 trains large language models with reinforcement learning to reason over knowledge graphs, cycling through think-query-retrieve-rethink steps for complex knowledge tasks.https://ramdi.fr/github-stars/gs-playground-high-throughput-photorealistic-simulation-for-vision-based-robot-learning/Sat, 23 May 2026 20:41:14 +0000https://ramdi.fr/github-stars/gs-playground-high-throughput-photorealistic-simulation-for-vision-based-robot-learning/GS-Playground combines 3D Gaussian Splatting rendering with a velocity-impulse physics engine to enable large-scale visual reinforcement learning at up to 10^4 FPS. Preview release with core simulation API and demos.https://ramdi.fr/github-stars/ml-from-scratch-exploring-machine-learning-fundamentals-with-pure-python-and-numpy/Sat, 23 May 2026 20:41:14 +0000https://ramdi.fr/github-stars/ml-from-scratch-exploring-machine-learning-fundamentals-with-pure-python-and-numpy/ML-From-Scratch offers bare-bones Python implementations of key machine learning algorithms using only NumPy, focusing on transparency over efficiency. Explore how it demystifies ML fundamentals.https://ramdi.fr/github-stars/ui-voyager-self-evolving-ai-agent-for-android-gui-automation-with-ssim-based-trajectory-correction/Mon, 04 May 2026 10:23:03 +0000https://ramdi.fr/github-stars/ui-voyager-self-evolving-ai-agent-for-android-gui-automation-with-ssim-based-trajectory-correction/UI-Voyager is a 4B parameter AI agent achieving 81% success on AndroidWorld by self-evolving with SSIM-based trajectory correction, no human labels needed.https://ramdi.fr/github-stars/deploying-rl-trained-motion-tracking-policies-on-legged-robots-with-motion-tracking-controller/Mon, 04 May 2026 10:23:02 +0000https://ramdi.fr/github-stars/deploying-rl-trained-motion-tracking-policies-on-legged-robots-with-motion-tracking-controller/motion_tracking_controller is a C++ ROS 2 package deploying RL-trained motion tracking policies on legged robots with ONNX inference and embedded robot control metadata.https://ramdi.fr/github-stars/finrl-trading-modular-weight-centric-quantitative-trading-with-deployment-consistent-backtesting-and-drl-portfolio-allocation/Mon, 04 May 2026 10:23:02 +0000https://ramdi.fr/github-stars/finrl-trading-modular-weight-centric-quantitative-trading-with-deployment-consistent-backtesting-and-drl-portfolio-allocation/FinRL-Trading offers a modular Python framework for quantitative trading focused on a weight-centric architecture unifying backtesting and live execution, with classical and DRL portfolio methods.https://ramdi.fr/github-stars/inside-alibabas-vrag-multimodal-retrieval-augmented-generation-with-dynamic-reasoning-graphs/Mon, 04 May 2026 10:23:02 +0000https://ramdi.fr/github-stars/inside-alibabas-vrag-multimodal-retrieval-augmented-generation-with-dynamic-reasoning-graphs/Alibaba’s VRAG models reasoning as a dynamic DAG with multimodal memory and RL-based fine-grained credit assignment, supporting text, image, and video retrieval in a unified framework.https://ramdi.fr/github-stars/trademaster-a-rigorous-reinforcement-learning-platform-for-quantitative-trading-research/Mon, 04 May 2026 10:23:02 +0000https://ramdi.fr/github-stars/trademaster-a-rigorous-reinforcement-learning-platform-for-quantitative-trading-research/TradeMaster offers a full pipeline for RL-based quantitative trading with 13+ algorithms and a rigorous 6-axis, 17-measure evaluation framework across multiple asset classes and trading tasks.https://ramdi.fr/github-stars/finrl-open-source-framework-for-financial-reinforcement-learning-with-a-train-test-trade-pipeline/Mon, 04 May 2026 10:23:01 +0000https://ramdi.fr/github-stars/finrl-open-source-framework-for-financial-reinforcement-learning-with-a-train-test-trade-pipeline/FinRL provides an open-source three-layer architecture for financial reinforcement learning with 5 DRL agents and 14+ data sources. Great for learning DRL in finance.https://ramdi.fr/github-stars/inside-toddlerbot-an-open-source-python-platform-for-multi-skill-humanoid-locomotion-with-depth-based-skill-classification/Mon, 04 May 2026 10:23:01 +0000https://ramdi.fr/github-stars/inside-toddlerbot-an-open-source-python-platform-for-multi-skill-humanoid-locomotion-with-depth-based-skill-classification/ToddlerBot offers a full Python stack for training, classifying, and deploying multi-skill humanoid locomotion policies using stereo depth data and reinforcement learning.