EmbodiedLab: Benchmarking Embodied Agents That Act to Know
EmbodiedLab, featured on Hugging Face Daily Papers, is a benchmark for agents that interact with their surroundings to achieve goals and understand them through changes in physical states.
Embodied agents are expected to accomplish real-world goals by deciding for themselves how and when to interact with their surroundings. For many such goals, changing the physical state of the world is the means rather than the end: the agent changes the state of a system through interaction, observes the feedback, and explores until it either achieves the goal itself (e.g., discovering physical laws) or learns what the goal requires; it acts to know.
Manipulation benchmarks stop at acting to change, with the target state given; scientific discovery benchmarks evaluate knowing but replace physical experimentation with symbolic actions or numerical queries. EmbodiedLab received 1 upvote on Hugging Face Daily Papers.
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