Sciweavers

Share
ATAL
2008
Springer

On k-optimal distributed constraint optimization algorithms: new bounds and algorithms

9 years 3 days ago
On k-optimal distributed constraint optimization algorithms: new bounds and algorithms
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' 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 constrain...
Emma Bowring, Jonathan P. Pearce, Christopher Port
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where ATAL
Authors Emma Bowring, Jonathan P. Pearce, Christopher Portway, Manish Jain, Milind Tambe
Comments (0)
books