Introduction

The Task-Adaptive Information Distribution (aka TAID) project addresses the problem of distributing information between collaborating people in dynamic situations. This project is a IOP-MMI (i.e. innovative research on Man Machine Interaction).

The project is divided into two parts; one part of the research will try to develop learning methods for assessing relevance of information for user's task based on the task characteristics, user characteristics and the workflow model. The other part the research focuses on an adaptive workflow model.

Our goal is to use existing learning methods to develop a trainable system for dynamic information distribution. Furthermore by adaptive workflow modeling we can distribute the processing load over the persons performing the task such that no single person becomes overloaded. Two main factors determine how information should be distributed: relevance for the task that the user is performing and the (information) load in his current and future tasks. Irrelevant information should be suppressed and if overload threatens the distribution and possibly the workflow should be adjusted. The processing load must be distributed over the persons performing the task such that no single person becomes overloaded.