Probabilistic modeling of human responses in complex interaction

We combine the strengths of human cognition and advanced bio-inspired computational search techniques to provide efficient and effective solutions to problems which neither can solve alone. We develop techniques combining advanced non-intrusive sensor measures of conscious and non-conscious behaviour during interaction tasks to enable very high level computerised support for human goal seeking in complex data and design environments. We use a user’s physiology and preference evaluation to capture their complex interaction with the data they view, probability models to accumulate info to identify their underlying preferences and extract relationships to find possible “hidden variables” which may help explain and leverage the user's choices.