aiqbench analysis
Cogentic represents a significant advancement in automated mathematical reasoning by employing a multi-agent architecture to iteratively prove and verify complex conjectures over extended horizons. By leveraging an orchestrator to manage independent provers and adversarial verification components, the system successfully solved five open problems in theoretical computer science and game theory that single-shot generation could not address. This work demonstrates how agentic workflows can effectively tackle research-level challenges requiring sustained logical exploration rather than immediate output.
Cogentic: Multi-Agent Orchestration for Automated Proof Discovery
arXiv:2609.40324v1 Announce Type: new Abstract: We present Cogentic, a multi-agent harness for automated proof discovery on open research problems. While frontier language models can generate strong mathematical ideas in a single shot, single-shot generation is often insufficient for open problems that require exploring multiple competing conjectures, overcoming subtle technical obstructions, and retaining intermediate progress over a long horizon. Cogentic addresses these challenges through an iterative prove--verify loop in which an orchestrator allocates a population of independent provers across distinct proof directions, subjects their output to adversarial verification by several specialized components, and promotes confirmed intermediate results into a persistent verified ledger that later rounds build on. The harness is designed to be able to solve research-level math and theoretical computer science problems. Using Gemini as the base model, Cogentic produced novel results on five open problems across online learning, auction theory, and mechanism design. Each result was independently verified by domain experts and is developed in full in companion papers. We list these results, and new ones as they are verified, at https://sites.google.com/view/cogentic .
Abstract:We present Cogentic, a multi-agent harness for automated proof discovery on open research problems. While frontier language models can generate strong mathematical ideas in a single shot, single-shot generation is often insufficient for open problems that require exploring multiple competing conjectures, overcoming subtle technical obstructions, and retaining intermediate progress over a long horizon. Cogentic addresses these challenges through an iterative prove--verify loop in which an orchestrator allocates a population of independent provers across distinct proof directions, subjects their output to adversarial verification by several specialized components, and promotes confirmed intermediate results into a persistent verified ledger that later rounds build on. The harness is designed to be able to solve research-level math and theoretical computer science problems. Using Gemini as the base model, Cogentic produced novel results on five open problems across online learning, auction theory, and mechanism design. Each result was independently verified by domain experts and is developed in full in companion papers. We list these results, and new ones as they are verified, at this https URL .
Artificial Intelligence (cs.AI); Computer Science and Game Theory (cs.GT)
arXiv:2609.40324 [cs.AI]
(or arXiv:2609.40324v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2609.40324 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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