Social scheduler: a proposal of collaborative personal task management

We propose a collaborative approach for personal task management which is modeled as an integration of alliance and human-in-the-loop model. Alliance model is based on information sharing and collaboration of several persons. They disclose their task condition and maintain to be updatable by their friends. To avoid privacy issues we propose emergent group discovery algorithm to control the level of disclosure. Human-in-the-loop model consists of three subsystems to support decision-making activities. Visualizer indicates the attributes associated with each task such as the deadline, the subjective priority, and the workload, which are determined by the user. Optimizer generates executable schedules from these tasks by active scheduler and multiobjective genetic algorithm. Recommender evaluates these alternatives by analytic hierarchy process. We implement client/server system called social scheduler on cell-phones environment. We remark the advantages of our approach with an experiment.