In the first part of the talk I will present navigation and wayfinding experiments in which we used virtual environments technology to systematically manipulate architectural features. To describe the spatial form of these environments we used isovist analysis. Isovists describe the visible area of a spatial situation from a given observer position and can be conceptualised as two-dimensional polygons which allows for the extraction of quantitative measures, such as the area, the longest lines of sight, local complexity, etc. Results from these experiments demonstrate that such isovist measures capture behaviourally relevant spatial and architectural features that can be used to predict navigation and orientation behaviour as well as gaze behaviour. I will argue that isovist and related architectural analysis methods such as space syntax are important techniques for developing an improved understanding of the relationship between architecture and behaviour. In the second part of the talk I will discuss dementia-friendly design principles and how neuropsychological theories of dementia and navigation can help to identify architectural features as well as design features that may compensate for dementia-induced declines in navigation abilities. Many people with dementia eventually move from their homes into unfamiliar retirement developments or care homes. Sadly, this change in circumstances occurs contemporaneously with a dementia-induced decline in navigational ability, which is particularly pronounced in unfamiliar environments. I will introduce current experimental approaches in which we systematically manipulate architectural and interior design features to identify how people with dementia learn to navigate unfamiliar environments using. Results of these experiments will be discussed in relation to current dementia-friendly design principles.
Prof Constantinos Daskalakis Constantinos Daskalakis is a Professor of Electrical Engineering and Computer Science at MIT, and a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds a Ph.D. in Computer Science from UC Berkeley, and an undergraduate diploma in Electrical and Computer Engineering from the National Technical University of Athens. Prior to joining MIT’s faculty, he was a postdoctoral researcher at Microsoft Research, New England. His research interests lie in theoretical computer science and its interface with economics, probability theory and statistics, and artificial intelligence. A main thrust of his work examines the computational foundations of Economics from a computational perspective, studying whether the predictions of economic theory are robust when agents interact in complex strategic environments and are computationally bounded. He is well-known for his paper ‘The Complexity of Computing a Nash Equilibrium,’ co-authored with Paul Goldberg and Christos Papadimitriou, where he shows that Nash equilibrium is computationally intractable. Nash equilibrium, introduced by John Nash in 1950, had been the crown jewel of equilibrium concepts in Economics for over half a century, inspiring the development of economics in the 20th century and winning John Nash a Nobel prize in economics in 1994. Daskalakis’s work shows that computational barriers may actually prevent Nash equilibrium to arise, calling the universality of Nash equilibrium into question. Daskalakis and his co-authors have been honoured with the 2008 Game Theory and Computer Science Prize by the Game Theory Society, and the 2011 Outstanding Paper Prize by the Society for Industrial and