World models are neural networks that learn an internal representation of an environment’s dynamics, enabling agents to simulate and plan within a learned latent space. They are used in model-based reinforcement learning, robotics, and autonomous decision-making.
A Curated List of Awesome Video World Models with AR Diffusion: Covering Algorithms, Applications, and Infrastructure, Aimed at Serving as a Comprehensive Resource for Researchers, Practitioners, and Enthusiasts.
a comprehensive and detailed AI study notes covering basic knowledge and various cutting-edge fields
Reflexive Intelligence: Decision-Making in Observer-Participant Environments (Zhang, 2026)
Reflective-Ethical Engine: Minimal cognitive architecture unifying perception, action, and consciousness
Empirical evidence that agent orchestration layers produce learnable cognitive dynamics in language models. 41.7% prediction improvement over persistence across 5 months of continuous operation. Built on OpenClaw.