Analogies: from Theory to Tools and Applications (AT2TA)

The AT2TA project (2023-2026) is a French national research project financed by the French National Research Agency (Agence Nationale de la Recherche – ANR) under grant ANR-22-CE23-0023.


Analogical reasoning is a remarkable capability of human reasoning. Analogical proportions are statements of the form “A is to B as C is to D”. They are the basis of analogical inference that has been used in machine learning (ML) tasks such as classification, decision making, and automatic translation with competitive results. Analogical extrapolation can solve hard reasoning tasks, such as IQ tests, and support data augmentation when learning models with few labeled samples. What makes analogical inference special is its unique ability to simultaneously process similarities and dissimilarities. Analogical reasoning links the two main axes of AI (knowledge representation and reasoning, and machine learning), and contributes to the transparency and explainability of AI as it is close to human reasoning and enables explanations based on examples and counter-examples.

This motivates our efforts to develop an analogy-based ML framework and to demonstrate its usefulness in real world applications. We will explore analogical reasoning for transfer learning and case-based reasoning, where the idea is to take advantage of what has been learned on a source domain in order to improve the learning process in a target domain related to the source domain. Suitable representations are the key to transfer the analogy-based framework to other settings and to handle different object types. This asks for a thorough study of representation spaces for analogy-based frameworks with different object types, not only textual and tabular, but also complex and structured, e.g., patient data, knowledge graphs and abstract syntax trees. As the final goal, the AT2TA project aims to provide an open access platform to detect, solve, and reason with analogies, illustrated by noteworthy applications in NLP, medical sciences, as well as in knowledge management and software engineering, which have a major impact in industry.

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