Multi-Context System for Optimization Problems


  • Tiep Le New Mexico State University
  • Tran Cao Son New Mexico State University
  • Enrico Pontelli New Mexico State University



This paper proposes Multi-context System for Optimization Problems (MCS-OP) by introducing conditional costassignment bridge rules to Multi-context Systems (MCS). This novel feature facilitates the definition of a preorder among equilibria, based on the total incurred cost of applied bridge rules. As an application of MCS-OP, the paper describes how MCS-OP can be used in modeling Distributed Constraint Optimization Problems (DCOP), a prominent class of distributed optimization problems that is frequently employed in multi-agent system (MAS) research. The paper shows, by means of an example, that MCS-OP is more expressive than DCOP, and hence, could potentially be useful in modeling distributed optimization problems which cannot be easily dealt with using DCOPs. It also contains a complexity analysis of MCS-OP.




How to Cite

Le, T., Son, T. C., & Pontelli, E. (2019). Multi-Context System for Optimization Problems. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 2929-2937.



AAAI Technical Track: Knowledge Representation and Reasoning