Declarative AI 2025

Abstract:  Logical English is a special form of English that computers can understand. It looks like regular English, but it follows stricter rules to avoid confusion. This allows us to write instructions or represent knowledge in a way that both people and computers can grasp. Think of it like a bridge between human language and computer code. It aims to be clear and readable, even for those without a tech background, while still being powerful enough to express complex ideas. Logical English achieves this by using a limited vocabulary and grammar, ensuring each word and sentence has a precise meaning. This structured approach makes it easier to translate into computer languages like Prolog, enabling computers to execute the logic we've written. This has exciting possibilities for various fields: Legal contracts, making them clearer and less ambiguous; knowledge bases, building systems that can reason and answer questions; education, teaching logic and programming in a more intuitive way. Essentially, Logical English is about making the power of computers more accessible by using a form of language we already understand.

About: Robert Kowalski is an Emeritus Professor at Imperial College London. His research is concerned with developing both human-oriented models of computing and computational models of human thinking. His early work, in the field of automated theorem-proving, contributed to the development of logic programming and Prolog. Later work, on the use of logic programming for knowledge representation and problem solving, includes contributions to the event calculus, legal reasoning, abductive reasoning, argumentation and the language LPS, which combines production systems with logic programs. Currently, he is working on the development and legal applications of the controlled natural language, Logical English, which is a form of syntactic sugar for Prolog and other logic programming languages. Kowalski is a Fellow of the AAAI, the EurAI, and the ACM. He received the 2011 IJCAI Award for Research Excellence “for his contributions to logic for knowledge representation and problem solving, including his pioneering work on automated theorem proving and logic programming”. He received the 2012 JSPS Award for Eminent Scientists, and he shared the Inaugural 2022 Stanford University CodeX Prize for his “ground-breaking work on the application of logic programming to the formalization and analysis of the British Nationality Act.

Abstract: RDFox is a commercial Datalog-enabled RDF management system that originated in academic research in the Knowledge Representation & Reasoning at Oxford University and is currently being developed by Oxford Semantic Technologies. In this talk, I will outline our journey of taking the basic research idea and bringing it into practice. Specifically, I will present an overview of the basic technical ideas that sparked the entire endeavour. I will further discuss the work that was needed to make the product commercially viable, such as API development, satisfying various enterprise-level requirements, guaranteeing system’s quality in the face of rising complexity. I will briefly discuss our experience in implementing the standards that RDFox is based on (i.e., RDF, OWL, SHACL, and so on). Finally, I will discuss various applications that use RDFox.

About: Boris is a Professor of Computer Science in the Department of Computer Science at the University of Oxford. His research interests span foundational aspects of the Semantic Web and logic-based knowledge representation, as well as the integration of reasoning with database technologies. He has made important contributions to reasoning in description logics and Datalog, and he developed the HermiT reasoner for the OWL family of languages. With Profs Ian Horrocks and Bernardo Cuenca Grau, he co-founded a university spinout called Oxford Semantic Technologies (OST). The spinout was acquired by Samsung in 2024, and its flagship product, the RDFox reasoning engine, is currently being integrated into Samsung’s portfolio of products. Motik received the 2013 Roger Needham award by the British Computer Society (BCS) and the 2007 Cor Baayen award by the European Research Consortium for Informatics and Mathematics (ERCIM), and he was selected as "2008 AI's 10 to Watch" by the IEEE Intelligent Systems magazine.

Abstract:  In robotic construction problems, multiple robots rearrange stacks of prefabricated blocks to build stable structures.  Even though automation can improve the efficiency and the productivity of certain construction tasks, the design of the structure to be built, planning of the robot motions, and proper ordering of robot actions are still decided manually in these approaches.   These problems are challenging for AI planning due to ramifications of actions, true concurrency, and requirements of supportedness of blocks by a surface or a robot and stability of the overall structure at all times.  In this talk, we will present  a general method to solve a wide range of robotic construction problems, based on Answer Set Programming integrated with state-of-the-art sampling-based motion planners and simulation-based physics engines.  We will illustrate the usefulness and applicability of this hybrid method over a set of challenging construction benchmark instances, using a bimanual Baxter robot.

About: Esra Erdem is a professor in computer science and engineering at Sabanci University, Istanbul. She received her Ph.D. in computer sciences at the University of Texas at Austin, and carried out postdoctoral research at the University of Toronto and Vienna University of Technology. Her research is in the area of artificial intelligence, in particular, the mathematical foundations of knowledge representation and automated reasoning, and their applications to various domains, including robotics, bioinformatics, logistics, and economics. Dr. Erdem was a general co-chair of ICLP 2013, a program co-chair of ICLP 2019, KR 2020 and PADL 2025, the general chair of KR 2021, and the president of KR Inc. She is an associate editor for Artificial Intelligence (AIJ) and Theory and Practice of Logic Programming (TPLP).