A Minimal Agent for Automated Theorem Proving

1. 1Build a minimal agentic baseline with iterative proof refinement, library search, and context management
2. 2Run experiments using qualitatively different benchmarks to evaluate the agent's performance
3. 3Configure and compare various frontier language models and design choices
4. 4Test the agent's ability to refine proofs iteratively
5. 5Apply the results to improve the design of AI-based theorem prover architectures

Researchers and AI engineers on a team can benefit from this approach to develop and compare different theorem prover architectures, and software engineers can apply this knowledge to improve the efficiency of their systems

💡 A minimal agentic baseline can enable systematic comparison across different AI-based theorem prover architectures

💡 Minimal agent for automated theorem proving achieves competitive performance using iterative proof refinement and library search