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The volume, developed within the MUHAI project ,offers an in-depth and integrated panorama of narratives and understanding in different disciplines and fields.   The book, edited by Luc Steels, builds upon recent insights and findings from social and cognitive sciences, humanities and other fields for which narratives have been found to play a relevant role in human sense and decision-making processes. The book retraces the existing narrative-centric studies in order to identify the most promising research streams for tomorrow’s AI.  From conceptual foundations of human-centric AI to pragmatics of language, touching narratives in economic and social affairs, historical sciences, clinical trials, social neurosciences and art interpretation the human narratives are explored in their relationship with AI.

This benchmark for recipe understanding in autonomous agents aims to support progressing the domain of natural language understanding by providing a setting in which performance can be measured on the everyday human activity of cooking. For this goal, the benchmark provides a number of recipes written in natural (human) English that should be converted to a procedural semantic network of cooking operations that can be interpreted and executed by autonomous agents.  The full benchmark has been made available standalone and as part of the Babel toolkit. Both options provide the same benchmark functionalities, but the Babel toolkit also provides the option of extending the system.

“The ultimate purpose of social sciences is to furnish causal explanations of classes of observable events, which are, at least in part, generated by individual and collective agency/action.” [1] The aim of a digital assistant for social history research is therefore to support social scientists with the construction of such causal explanations for observable events, also theories or hypotheses.