HYDRA 2024

Welcome to the 3rd International Workshop on HYbrid models for coupling Deductive and inductive ReAsoning (HYDRA).
The workshop is co-located with the 27th European Conference on Artificial Intelligence (ECAI 2024). 

Scope of the workshop

Deductive reasoning has been widely used in various fields such as planning, scheduling, robotics, and other industrial applications due to its ability to derive specific conclusions based on valid evidence or facts. However, deductive reasoning requires consistent premises and a proper knowledge base to make accurate inferences. On the other hand, inductive reasoning, such as Machine and Deep Learning, extracts generalized conclusions from limited and specific observations. While these approaches are promising in recognizing meaningful patterns from large amounts of data, they lack means for interpreting the model's choices and incorporating prior knowledge. Therefore, combining and intertwining deductive and inductive methods can offer a more comprehensive approach to Artificial Intelligence, leveraging the strengths of both methods

Motivations and Main Goals

The HYDRA workshop seeks to bridge the gap between deductive and inductive reasoning, which are two powerful but distinct methods in artificial intelligence. While deductive reasoning relies on explicit premises and logical inference rules to derive specific conclusions, inductive reasoning infers generalizations from observations, often with the help of Machine Learning and Deep Learning techniques. To combine these approaches paves the way for potentially creating more robust and flexible Artificial Intelligence (AI) systems which can reason effectively in a variety of contexts. Nevertheless, neither deductive nor inductive reasoning methods cannot be considered the ultimate, comprehensive solutions to AI. Therefore, to study how they can be intertwined advantageously enables the development of new solutions which can take into account the peculiarities and strengths of the two methods. 

Within HYDRA, we welcome submissions of original research on all aspects of hybrid deductive-inductive reasoning, including theoretical frameworks, practical applications, and experimental results. We are interested in approaches that address key challenges in this area, such as developing methods for integrating logical and statistical models, designing algorithms that can reason with incomplete or uncertain knowledge, and creating tools for explaining and interpreting hybrid models. We also encourage work that investigates the ethical and social implications of these technologies, including issues related to fairness, accountability, and transparency. 

The HYDRA workshop aims at bringing together the scientific community, and welcomes both theoretical and practical papers on frameworks, applications, and methods for integrating and combining deductive and inductive systems in different scenarios, to any extent. The workshop also welcomes summaries of recently published papers, as well as work-in-progress contributions. HYDRA returns from its first successful edition and welcomes further contributions. 

Keywords

• Logic programming,

• Deductive Reasoning,

• Inductive Reasoning,

• Abductive Reasoning

• Hybrid reasoning models,

• Deep Learning,

• Machine Learning,

• Neuro-Symbolic methods