Tag: Agent Learning
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Web world models: giving AI agents persistent environments to explore
What are web world models? Web world models are a novel approach to training and testing artificial intelligence in environments that remain consistent over time. Instead of relying on a single static dataset or a series of isolated simulations, these models define the rules of a simulated web-like universe, while a language model fills that…
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Web World Models: Persistent Environments for AI Agents
Reimagining AI exploration with persistent web worlds Researchers from Princeton University, UCLA, and the University of Pennsylvania are advancing a bold idea: give AI agents stable, persistent worlds to explore. By combining conventional web code that defines the rules of a simulated environment with a powerful language model that populates those worlds with stories, tasks,…