Resilient Computing Curriculum

This Deliverable presents the MSc Curriculum in Resilient Computing suggested by ReSIST. It includes the description of the syllabi for all the courses in the two semesters of the first year, those for the common courses in semester 3 in the second year together with an exemplification of possible application tracks with the related courses. This MSc curriculum has been updated and completed taking advantage of a large open discussion inside and outside ReSIST. This MSc Curriculum is on-line on the official ReSIST web site, where all information is available together with all the support material generated by ReSIST and all other relevant freely available support material.European Commission through NoE IST-4-026764-NOE (ReSIST

Resilient Computing Courseware

This Deliverable describes the courseware in support to teaching Resilient Computing in a Curriculum for an MSc track following the scheme of the Bologna process. The development of the supporting material for such a curriculum has required a rather intensive activity that involved not only the partners in ReSIST but also a much larger worldwide community with the aim of identifying available updated support material that can be used to build a progressive and methodical line of teaching to accompany students and interested persons in a profitable learning process. All this material is on-line on the official ReSIST web site http://www.resistnoe.org/, can be viewed and downloaded for use in a class and constitutes, at our knowledge, the first, almost comprehensive attempt, to build a database of support material related to Dependable and Resilient Computing.European Commission through NoE IST-4-026764-NOE (ReSIST

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)