Research group Human agents and intelligent software agents seldom act in solitude, most of the time they need to coordinate themselves, cooperate and collaborate to achieve goals. Cognitive and social capabilities are forming the basis for the agents’ ability to represent knowledge, learn, reason, make decisions and autonomously act to pursue common goals in collaboration, or negotiate and reach agreements in the case of conflicting goals.
Digital companions are an example of such agents that may support and enhance the human's capacity in conducting activity.
We develop theories and methods in a multidisciplinary setting, including formal argumentation, formal dialogue systems, answer set programming, methods for user modeling, user adaptation, and personalization. Theories about human activity, motivation, emotions and cognition are forming a base for developing new architectures, software and interfaces for socially intelligent agents and interactive intelligent systems. Activity and intention detection, as well as activity reasoning including motives, motivation, preferences and goals are necessary to allow the system to support the human and enhance the human's capacity in conducting meaningful activities.
Our research ranges from formal and theoretical research to applied research, mainly in the medical and health domains, for instance, as diagnostic decision-support or as reasoning support when behavior change is essential for improving health and wellbeing. Read more following the links below.
If you are interested in AI, you are welcome to participate at Autograide Hackaton on the 19th of January.
Want to improve plant nutrient uptake with new machine learning and AI methods.
Funded by the Childhood Cancer Fund, Tommy Löfstedt will automate radiation therapy in pediatric oncology.
Read more about Collaborative AI Lab.
Formal Reasoning Methods
