Constraint Programming for Hierarchical Resource Allocation

Constraint Programming for Hierarchical Resource Allocation

Typical for self-organizing, adaptive systems is their ability to reconfigure and make certain decisions to improve its operating state with respect to several quality criteria. Constraint programming is a suc- cessful paradigm rooting in mainstream artificial intelligence designed to model a variety of decision problems and solve them with generic algo- rithms. Integration of both worlds promises interesting application and research areas. If constraints describing valid states are available in a system’s specification, these constraints are useful to steer reconfigura- tions if the system transitions to an invalid state. We give an overview of existing techniques to use constraint programming in collective systems and consider future extensions.
published 2014 Proceedings of the Second Organic Computing Doctoral Dissertation Colloquium, 2014