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Next Generation Computer Assisted Reasoning

Project description

Enabling the future of computer assisted Automated Reasoning

Among the many fields of modern Automated Reasoning (AR) and AI, the automation of complex mathematical reasoning, a key aspect of most sciences and technology, is among the biggest challenges. In contrast to human experts, the AR and theorem-proving paradigms are mostly one-sided, lacking the ability to combine reasoning, conjecture, and learning in complex feedback loops that are expected to be key in the next generation of AR systems for mathematics. The ERC-funded NextReason project aims to design new AI approaches, innovative methods, autonomous systems and revolutionary logic-aware learning architectures and neuro-symbolic methods which will enable the next generation of AR systems.

Objective

Galileo said that mathematics is the language of science. It is used to solve arbitrary abstract problems, underpinning hard sciences, technology and engineering. Automation of complex mathematical reasoning, discovery and large-scale formal proofs is today one of the greatest challenges in the fields of Automated Reasoning (AR) and Artificial Intelligence (AI).

Compared to human experts, today’s main automated reasoning and theorem proving paradigms are severely one-sided: they largely lack the capability to combine learning, reasoning and conjecturing in complex feedback loops. There is solid evidence that such combinations are the key to building the next generation of advanced reasoning systems for mathematics, computer-assisted proof and formal verification.

The NextReason project will create one of the world’s strongest teams working on such combinations. We will jointly develop
(i) logic-aware learning architectures and neuro-symbolic methods for a range of automated and interactive theorem proving paradigms,
(ii) novel AI approaches for learning-guided automated decomposition of hard reasoning problems,
(iii) methods for automated formalization of human-written mathematics by combining learning-based translation methods with semantic methods such as type-checking and theorem proving,
(iv) neuro-symbolic methods for synthesis of interesting mathematical objects, conjectures and explanations, and
(v) autonomous systems and positive feedback loops interleaving learning, theory exploration and efficiently guided proof search to attack hard and open problems.

The expected overall outcome is a new generation of strong architectures for reasoning and theorem proving, and their transformative effect on large-scale computer-assisted proof, mathematics and formal verification.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2024-ADG

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Host institution

GOETEBORGS UNIVERSITET
Net EU contribution

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€ 1 500 000,00
Address
VASAPARKEN
405 30 Goeteborg
Sweden

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Region
Södra Sverige Västsverige Västra Götalands län
Activity type
Higher or Secondary Education Establishments
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Total cost

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Beneficiaries (3)

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