The HYDRA workshop seeks to bridge the gap between deductive and inductive reasoning, which are two powerful but distinct methods in Artificial Intelligence (AI). 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. Combining these approaches paves the way for potentially creating more robust and flexible AI systems that can reason effectively in various contexts. Nevertheless, neither deductive nor inductive reasoning methods can be considered the ultimate, comprehensive solutions to AI. Therefore, studying how they can be intertwined advantageously enables the development of new solutions that 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 these technologies' ethical and social implications, 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 previous successful editions and welcomes further contributions.

Submission Guidelines

Authors are invited to submit their manuscripts in PDF via the EasyChair system at the link: https://easychair.org/conferences/?conf=hydra2026.

The workshop welcomes both full papers, possibly already submitted to other conferences or journals, and short papers, which are suggested for presenting work in progress, extended abstracts, software prototypes, or general overviews of research projects. The workshop also welcomes position and discussion papers.

All submissions must be in PDF format, written in English, and formatted according to the LNCS format (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines). Full papers should not exceed 13 pages (including bibliography); short, position, and discussion papers should not exceed 6 pages (including bibliography). To ease the reviewing process, the authors of full papers may add an appendix (although reviewers are not required to consider it in their evaluation).

List of Topics

• Hybrid inductive-deductive approaches to AI
• Interaction of inductive and deductive techniques for AI solutions
• Integration of Answer Set Programming (ASP) in inductive scenarios
• Integration of Constraint Programming (CSP) in inductive scenarios
• Integration of other logic programming paradigms in inductive scenarios
• Integration of declarative solutions in inductive scenarios
• Logic programming language extensions for supporting inductive processes
• New methods for coupling peculiarities of deductive and inductive systems
• Inductive reasoning to enhance and improve deductive systems
• Deductive processes for intensive data flow management
• Deductive processes in strong inductive-tailored scenarios
• Knowledge representation and reasoning for improving and enhancing inductive processing
• Discussions and positions on novel hybrid methods of deductive and inductive reasoning
• Evaluation and comparison of existing deductive and inductive methods
• Hybridizing logic programming paradigms with procedural approaches
• Novel contexts of application for hybrid deductive and inductive systems
• Coupling reasoning with Large Language Models
• Integrating reasoning in Retrieval-Augmented Generation.

Committees

Steering Committee Chairs

• Francesco Calimeri, University of Calabria (Italy)

• Giorgio Terracina, University of Calabria (Italy)

General Chairs

• Pierangela Bruno, University of Calabria (Italy)

• Francesco Cauteruccio, University of Salerno (Italy)

Program Chairs

• Edoardo De Rose, Karlsruhe Institute of Technology (Germany)
• Cinzia Marte, University of Calabria (Italy)

Program Committee

Coming Soon!

Venue

Klagenfurt, Austria

7 - 11 September 2026