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A reimplementation of [DreamerV3][paper], a scalable and general reinforcement learning algorithm that masters a wide range of applications with fixed hyperparameters.
The main features of danijar/dreamerv3 are: Embodied World Models.
Projects with overlapping indexed features include: agibottech/ewmbench — Official code for EWMBench: Evaluating Scene, Motion, and Semantic Quality in Embodied World Models. aidanscannell/dcmpc — This repository is the official implementation of DC-MPC, presented in "Discrete Codebook World Models for Continuous… alibaba-damo-academy/worldvla — RynnVLA-002: A Unified Vision-Language-Action and World Model. anh-nn01/time-aware-world-model — ⏱️ Time-Aware World Model 🌎 🎓 Paper | 📌 Poster | 🌐 Website | 🎬 Videos. aria-zhangjl/storyweaver — This is an official implementation of AAAI 2025 paper StoryWeaver: A Unified World Model for Knowledge-Enhanced Story… 20robo/raenwm — Paper | Models (Coming Soon).
Official code for EWMBench: Evaluating Scene, Motion, and Semantic Quality in Embodied World Models
This repository is the official implementation of DC-MPC, presented in "Discrete Codebook World Models for Continuous Control" at ICLR 2025. DC-MPC is a model-based reinforcement learning algorithm demonstrating the strengths of learning a discrete latent space with discrete codebook encodings.
RynnVLA-002: A Unified Vision-Language-Action and World Model
