Tag: reinforcement learning

ProtoMotions3 is a GPU-accelerated framework for training physically simulated digital humans and humanoid robots, supporting IsaacLab, MuJoCo, and Newton with validated sim-to-real deployment to Unitree G1.

Discover how AgentGym-RL trains 7B parameter LLM agents to surpass GPT-4o on real-world multi-turn tasks using progressive horizon scaling reinforcement learning. Complete setup guide, code examples, and performance benchmarks included.

Stop wasting money on bad trading bots. Discover Awesome-Quant-Machine-Learning-Trading, the ruthlessly curated resource collection that elite quantitative developers use to build profitable ML-driven trading systems. From de Prado's foundational techniques to production-ready RL environments.

Discover awesome-ai-in-finance: the most comprehensive curated repository of AI-powered financial tools, strategies, and research. From autonomous trading agents to LLM-powered analysis, this 200+ resource collection helps developers build systems that survive real markets.

UW Lab is a unified robotics research platform built on NVIDIA Isaac Lab, offering cleaned environments, lab-tested sim-to-real configurations, and OmniReset for manipulation without reward engineering. Learn installation, code examples, and why researchers are switching.

WarAgent is an LLM-powered multi-agent system that simulates World War I, World War II, and ancient Chinese conflicts using GPT-4 and Claude-2. Discover how AI agents recreate historical decision-making and what this reveals about preventing future wars.

TensorTrade is the open-source RL framework for training robust trading agents. Discover why its transparent research on commission costs and modular architecture makes it essential for serious quantitative developers.