Abstract
Distributed Constraint Optimization Problems (DCOPs)can be optimally solved by distributed search algorithms,such as ADOPT and BnB-ADOPT. In centralized solv-ing, maintaining soft arc consistency during search has proved to be beneficial for performance. In this thesis we aim to explore the maintenance of different levels of soft arc consistency in distributed search when solving DCOPs.