Integrating learning and reasoning, i.e. endowing algorithms that learn from experience with the ability to consult existing knowledge and reason with what has already been learned, constitutes one of the key open questions in AI. It holds the potential of addressing many of the shortcomings of contemporary AI approaches, including the black-box nature and the brittleness of deep learning, and the difficulty to adapt knowledge representation models in the light of new data.

Integrating learning and reasoning calls for approaches that combine knowledge representation and machine reasoning techniques with learning algorithms from the fields of neural, statistical and relational learning. IJCLR 2020 brings together, for the first time, four international conferences and workshops addressing such research topics: The 30th International Conference on Inductive Logic Programming (ILP); The 15th International Workshop on Neural-Symbolic Learning & Reasoning (NeSy); The 10th International Workshop on Statistical Relational Artificial Inteligence (StarAI); The 10th International Workshop on Approaches and Applications of Inductive Programming (AAIP). In addition to each of the four events’ individual programs, which will be held in parallel, IJCLR 2020 aims to promote collaboration and cross-fertilization between different approaches and methodologies to integrating learning & reasoning, via joint keynotes, panel discussions and poster sessions.

Conference website : http://lr2020.iit.demokritos.gr