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OpenHail is an open-source Gymnasium environment for simulating and controlling electric ride-hailing fleets using reinforcement learning. It supports event-driven and hybrid control strategies for joint assignment, repositioning, and charging decisions.
A hands-on guide to learning reinforcement learning from scratch, focusing on the CartPole environment using PyTorch and Stable Baselines3 libraries.
Introduces Building2Building (B2B), a large-scale benchmark for studying generalization and transfer in reinforcement learning using realistic HVAC control environments built on EnergyPlus, compatible with Gymnasium.
OpenEnv, a framework for creating and deploying isolated execution environments for agentic RL training, has moved to Hugging Face and is now governed by a committee including Meta-PyTorch, NVIDIA, and others.
This paper presents MuJoCo-Drones-Gym, a GPU-accelerated multi-drone simulator built on MuJoCo that supports flexible physics models, action interfaces, and observation spaces for reinforcement learning and control research.
A 6-DoF rocket guidance, navigation, and control (GNC) simulation environment built using Gymnasium, designed for developing and testing GNC algorithms by popping balloons in a realistic physics simulation.