I am happy to announce that I have received a grant for the BehavE project proposal (Behaviour Understanding through Situation Models for Situation-aware AssistancE) from the German Research Foundation (DFG). The project will start next year and will continue for three years. The project builds on the Text2HBM project and its objective is the investigation of algorithmic solutions to learning situation models (SM) from heterogenous data. SMs represent domain knowledge in a structured and consolidated manner. These models are used for reasoning about the person’s behaviour, needs and assistance strategies.

To achieve the project objectives, the approach will combine existing and novel methods that address different problems of knowledge extraction and model learning from heterogenous sources. They include supervised and unsupervised techniques for semantics extraction and relations discovery; making use of existing structured knowledge to improve the discovered semantics, reinforcement learning techniques for adapting the situation model, as well as various machine learning techniques for maintaining the model and learning the model heuristics. To evaluate the approach, the learned models will be applied to existing datasets from the elderly care and healthcare domains.

The proposed approach will allow us to reduce the need of expert knowledge and manual development by replacing it with automatically extracted models. If successful, the approach will reduce the time and resources needed for building rich high quality situation models and for developing any system that relies on domain knowledge in order to reason about the solution of a given problem.