This paper addresses the application of distributed constraint optimization problems (DCOPs) to large-scale dynamic environments. We introduce a decomposition of
DCOP into a graphical game and investigate the evolution of various stochastic and deterministic algorithms. We
also develop techniques that allow for coordinated negotiation while maintaining distributed control of variables. We
prove monotonicity properties of certain approaches and
detail arguments about equilibrium sets that offer insight
into the tradeoffs involved in leveraging efficiency and solution quality. The algorithms and ideas were tested and
illustrated on several graph coloring domains.