How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Dopamine is a reinforcement learning research framework designed for prototyping and testing algorithms across diverse simulated environments. It provides an agent development toolkit that utilizes a flat class hierarchy to facilitate the creation and extension of learning agents. The framework includes a standardization layer via environment wrappers that connect agents to various physics simulations and gaming environments. It also features a high-performance experience replay buffer for storing and sampling transition data to improve training stability, alongside a dedicated hyperparameter
Habitat-Lab is an open-source platform for training and evaluating embodied AI agents in photorealistic 3D indoor environments. It functions as a high-performance 3D indoor environment simulator that supports physics-based interaction, enabling research into navigation and manipulation tasks. The platform provides a modular task-environment abstraction that separates task logic from environment simulation, using configuration-driven pipeline assembly to compose simulation and training pipelines. It includes a hierarchical sensor-actuator architecture for mixing and matching perception and act
ROLL is a distributed reinforcement learning framework and model alignment toolkit designed for large language models. It serves as a scalable training pipeline and GPU cluster manager, providing the infrastructure to align model behavior using reinforcement learning algorithms and preference optimization techniques. The project distinguishes itself through an agentic rollout orchestrator that generates and collects multi-turn interaction trajectories between AI agents and simulated environments. It supports specialized alignment methods including Direct Preference Optimization, reinforcement
The main features of langfengq/verl-agent are: Dense Reward Optimization, Reinforcement Learning Frameworks.
Projects with overlapping indexed features include: google/dopamine — Dopamine is a reinforcement learning research framework designed for prototyping and testing algorithms across diverse… facebookresearch/habitat-lab — Habitat-Lab is an open-source platform for training and evaluating embodied AI agents in photorealistic 3D indoor… alibaba/roll — ROLL is a distributed reinforcement learning framework and model alignment toolkit designed for large language models.… aunum/gold — Reinforcement Learning in Go. chainer/chainerrl — ChainerRL is a deep reinforcement learning library built on top of Chainer. amap-ml/tree-grpo — Tree Search for LLM Agent Reinforcement Learning.
