Grammatical Inference (GI) studies machine learning algorithms for various language related models such as automata and grammars. Historically, these models are used, for instance, to understand natural language and to do computational linguistics. At the same time, these kind of models are also a major research topic within the ICALP community. These models are central in understanding recursive computations and their expressive power and complexity. In recent years we have seen some important results starting to bridge the gap between both worlds, including applications of learning to formal verification and model checking, (co-)algebraic formulations of automata and grammar learning algorithms and theoretical foundations of learning. The aim of this workshop is to bring together experts on language theory that could benefit from grammatical inference tools, and researchers in grammatical inference who could find new insights for their methods in theoretical computer science.