Autonomous Science Bench: Evaluating AI Agents for Autonomous Scientific Discovery

The paper introduces Autonomous Science Bench, a benchmark for AI agents that must choose experiments under a limited budget. It features six real-world design-build-test-learn campaigns in biology, chemistry, and materials science, where agents select design batches, receive lab measurements, and iteratively refine a predictive model. Success is measured by two calibrated gates—discovery and learning—highlighting distinct agent weaknesses that overall success rates alone would mask.

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• agents
• benchmarks