System for Robust Mathematical Claim Verification with GPT-5
Build an AutoGen multi-agent system designed for rigorous verification of complex mathematical claims or proofs. This challenge requires implementing an Agent-to-Agent (A2A) protocol for collaborative problem-solving among agents. A 'Prover' agent, powered by GPT-5, will generate initial claims or proofs. A 'Challenger' agent and a 'Refiner' agent will then collaboratively attempt to verify, find flaws, or improve the proofs, leveraging external tools for symbolic computation and employing adaptive reasoning budgets to tackle intricate mathematical problems.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop an AutoGen multi-agent system using GPT-5 that employs A2A communication and adaptive reasoning to rigorously verify complex mathematical claims and proofs.
How work is evaluated
Evaluation will focus on the system's ability to accurately verify mathematical claims, identify errors in flawed proofs, and effectively utilize external tools and collaborative agent interactions.
Challenge datasets
Public datasets, plus the private datasets you have access to.
What you should walk away with
Integrate GPT-5 as a core 'Prover' agent and orchestrate other agents for verification and refinement.
Implement A2A protocol for secure and efficient agent-to-agent communication in a verification context.
Master AutoGen for designing flexible multi-agent conversational systems for complex problem-solving.
Develop agents capable of employing adaptive reasoning budgets and leveraging external mathematical tools.
Reference links and supporting material
Sample data for 2 tasks
Challenge setup
Evaluation will focus on the system's ability to accurately verify mathematical claims, identify errors in flawed proofs, and effectively utilize external tools and collaborative agent interactions.
Challenge input
{'claim': 'For any real numbers a and b, if a^2 = b^2, then a = b.'}
Agent execution
No agent tool is listed for this challenge.
Evaluated output
{'verification_result': 'False', 'reasoning': '...', 'steps': ['...'], 'tools_used': ['...']}
- Checks if the output is a valid JSON adhering to the specified format.
- Ensures the system's final verification result (True/False) matches the actual correctness of the claim/proof.
- Reasoning Clarity Score target: 8
- Python execution harness
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
No tool records are attached.
Evaluation contract
- Checks if the output is a valid JSON adhering to the specified format.
- Ensures the system's final verification result (True/False) matches the actual correctness of the claim/proof.
Metrics
- Reasoning_Clarity_Score · Target 8
- Error_Detection_Accuracy · Target 9
- Tool_Utilization_Effectiveness · Target 7
- Collaboration_Efficiency · Target 7
Workflow tasks
- Task 1
Input: {'claim': 'For any real numbers a and b, if a^2 = b^2, then a = b.'}
Output: {'verification_result': 'False', 'reasoning': '...', 'steps': ['...'], 'tools_used': ['...']}
Execution harness: Python
- Task 2
Input: {'flawed_proof': 'Prove that 1 = 2:\nLet a = b.\nThen a^2 = ab.\na^2 - b^2 = ab - b^2.\n(a-b)(a+b) = b(a-b).\nDivide both sides by (a-b): a+b = b.\nSince a = b, substitute b for a: b+b = b.\n2b = b.\nDivide by b: 2 = 1.'}
Output: {'error_found': 'True', 'error_location': 'Line 5: Division by zero', 'explanation': '...', 'correct_conclusion': '...'}
Execution harness: Python
Recipe freeze marker
No recipe freeze time is recorded.