Midterm evaluation Research 2016-2018:

The research of TU Delft’s Faculty of Architecture and the Built Environment (Faculteit Bouwkunde) covers the full spectrum of design, engineering, planning, and management of the built environment. Its research portfolio comprises the research that is conducted by four departments: Architecture Architectural Engineering + Technology (AE+T) Management in the Built Environment (MBE) Urbanism The faculty’s research focusses specifically at improving the design and performance of buildings, districts, cities and regions in order to better meet the requirements and expectations of their users and communities. From that perspective, much of the research that is conducted can be understood as applied science, appealing to the curiosity and the needs of other researchers, practitioners and the broader public alike. The research is a blend of humanities, social and engineering sciences. The humanities are strongest represented in the Architecture department, social sciences in the MBE and Urbanism departments, while the engineering sciences find their strongest representation in AE+T

Computational intelligence in decision making

In this preface we stress the relevance of the traditional collaboration between Engineering and any field of Mathematics in order to build intelligent decision-aid tools, as it is illustrated by the twelve papers contained in this Special Issue. These papers, selected by means of a standard peer review process after an open call, offer an interesting variety of models, approaches and techniques, to be applied within different specific problems. Each paper is introduced in this preface and is developed in the subsequent article. Moreover, in this preface we also claim for a more intense collaboration between decision engineers and other fields that study human brain behavior, like Neurology, Psychology, Sociology and Linguistics. Because if we really want to procure intelligent tools for decision aid, we should start by taking the human brain as our first reference, as it is the most efficient machinery we have found in order to deal with complex, uncertain, incomplete and even apparently inconsistent information. We hope that readers will enjoy this Special Issue devoted to Computational Intelligence in Decision Making

Handbook on Computational Intelligence

With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of ‘digital obesity’. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas - from social sciences, economics and biology, medicine and social networks, to cyber security. The Handbook of Computational Intelligence (in two volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems. This work is a “one-stop-shop” for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike