Pervasive model adaptation: the integration of planning and information gathering in dynamic production systems

Model-based planning often presumes a static system model, while in practice physical systems may evolve or drift over time. This paper proposes the idea of pervasive learning in a production system, where the model is dynamically updated using production output. The core idea is the interplay between model learning and production planning. We seek plans which simultaneously serve the goals of achieving high productivity for production and information gathering for model learning. The paper uses a simple modular printing example to illustrate issues such as formulation of the information criterion and search strategy for informative plans. The idea of pervasive learning can be further extended to achieve long term productivity in production systems.

Citation

Liu, J. J.; Kuhn, L.; de Kleer, J. Pervasive model adaptation: the integration of planning and information gathering in dynamic production systems. 19th International Conference on Automated Planning and Scheduling (ICAPS '09); 2009 September 19-23; Thessaloniki, Greece. Menlo Park, CA: AAAI Press; 2009.