International Conference on Modelling Decisions for Artificial Intelligence

Overview

The 23rd International Conference on Modeling Decisions for Artificial Intelligence. In MDAI we are particularly interested in the different facets of decision processes in a broad sense. This includes model building and all kind of mathematical tools for data aggregation, information fusion, and decision making; tools to help decision in data science problems (including e.g., statistical and machine learning algorithms as well as data visualization tools); and algorithms for data privacy and transparency-aware methods so that data processing processes and decisions made from them are fair, transparent, explainable and avoid unnecessary disclosure of sensitive information. The MDAI conference includes tracks on the topics of (i) data science and machine learning, (ii) data privacy, (iii) aggregation functions, (iv) human decision making, (v) graphs and (social) networks, and (vi) information security. The conference has been since 2004 a forum for researchers to discuss last results into these areas of research. MDAI is rated as a CORE B conference by the Computing Research and Education Association of Australasia - CORE. Publication: Proceedings with accepted papers are to be published in the LNAI/LNCS series (Springer-Verlag) and distributed at the conference. Original technical contributions are sought. Contributions will be selected on the basis of their quality. Papers will be evaluated by at least two reviewers. One full registration will cover at most two published paper. Papers should be sent as an attached PDF file to mdai@mdai.cat (with cc to vicenc.torra@umu.se). Length and format: Submitted papers should follow LNCS/LNAI style files. Camera-ready versions of accepted papers should be at most 12 pages long.

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