VQV Signal
EmbodiedEvo proposes using executable code as a representation for physical intelligence in general-purpose agents, enabling explicit and reusable control logic. This approach contrasts with vision-language-action models by making code both the policy and the problem-solving workspace.
EmbodiedEvo proposes using executable code as a representation for physical intelligence in general-purpose agents, enabling explicit and reusable control logic. This approach contrasts with vision-language-action models by making code both the policy and the problem-solving workspace.
AI-assisted summary based on the listed source.
Bringing general-purpose agents into the physical world calls for an executable representation of physical intelligence. Compared with vision-language-action (VLA) models, which map observations and language instructions directly to actions, code makes control logic explicit and reusable. Code can serve not only...
Using code as a control logic representation allows agents to better handle physical tasks with reusable and explicit policies. This method could improve how AI agents operate in the physical world by enhancing task-solving capabilities.
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