Cognitive Science & Artificial Intelligence
The research program CS&AI concerns itself with the computational modelling of cognitive processes in the visual, linguistic, and ludological domains. Research in the program is predominantly empirical and automatic; through machine learning, computers induce models from data. By manipulating the representation of the tasks to be learned, the experimenter can use the experiments to induce new theories (by using knowledge-free representations) as well as validate existing theories (by adopting theory-driven representations). Although research in the group fully adopts the entire toolbox of machine learning methods, there is also a longstanding home-grown interest in the usage and development of memory-based (example-based, k-nearest neighbour) learning algorithms.
In the visual domain, highlight interests are the recognition of the 'fingerprint' of master painters, texture classification, object and face recognition, facial dynamics analysis, and the detection of outliers through dimension reduction and dissimilarity metrics. In the linguistic domain, work is performed in automatic machine translation, word sense disambiguation, paraphrasing, text analytics, and text correction. In the ludological domain (games studies), research focuses on opponent modeling, developing artificially intelligent computer players, and measuring entertainment in games.
The mission of the Creative Computing research program is to narrow the gap between humans and computers. This program is centered around the question "Will we ever be able to interact with computers in a totally familiar and natural way?" This question indicates that the Creative Computing program focuses on people as well as computers. This focus is also becomes clear after taking the program's multidisciplinary fields of research into account. Creative Computing combines the use of research methodologies, borrowed from artificial intelligence, datamining, serious gaming, psychology and linguistics, with computer science. The studies in the projects make use of experimentally elicited materials and of corpora with naturally occurring data. They focus on the behavior of both the sender and the receiver in descriptive, cognitive, and functional analyses through the use of various techniques such as questionnaires, production and perception experiments, computational modeling, behavioral observations, corpus analyses.
There is a strong emphasis on collaborative research within the programme, and many publications are co-authored. In addition, PhD projects are commonly supervised by at least two senior researchers. Besides a common research focus on creative computing and communication, researchers also share a common data-driven research methodology, which is often experimental in nature. Many researchers have a psychological or technical background, which is translated into a human-centered approach.
Research results are disseminated via scientific publications (preferably in A journals and top conferences). Valorization occurs via different routes, including through a close link between research and teaching.