@conference {1508522,
	title = {On K-Optimal Distributed Constraint Optimization Algorithms: New Bounds and Algorithms },
	booktitle = {The Seventh International Conference on Autonomous Agents and Multiagent Systems},
	year = {2008},
	abstract = {Distributed constraint optimization (DCOP) is a promising approach
to coordination, scheduling and task allocation in multi agent networks. In large-scale or low-bandwidth networks, finding the global
optimum is often impractical. K-optimality is a promising new approach: for the first time it provides us a set of locally optimal algorithms with quality guarantees as a fraction of global optimum. Unfortunately, previous work in k-optimality did not address domains
where we may have prior knowledge of reward structure; and it
failed to provide quality guarantees or algorithms for domains with
hard constraints (such as agents{\textquoteright} local resource constraints). This
paper addresses these shortcomings with three key contributions.
It provides: (i) improved lower-bounds on k-optima quality incorporating available prior knowledge of reward structure; (ii) lower
bounds on k-optima quality for problems with hard constraints; and
(iii) k-optimal algorithms for solving DCOPs with hard constraints
and detailed experimental results on large-scale networks.},
	author = {Bowring, Emma and Jonathan P. Pearce and Christopher Portway and Jain, Manish and Tambe, Milind}
}
