Sensitivity analysis for distributed optimization with resource constraints

Previous work in multiagent coordination has addressed the challenge of planning in domains where agents must optimize a global goal, while satisfying local resource constraints. However, the imposition of resource constraints naturally raises the question of whether the agents could significantly improve their team performance if a few more resources were made available. Sensitivity analysis aims to answer that question. This paper focuses on sensitivity analysis in the context of the distributed coordination framework, Multiply-Constrained DCOP (MC-DCOP). There are three main challenges in performing sensitivity analysis: (i) to perform it in a distributed fashion, (ii) to avoid re-solving an NP-hard MC-DCOP optimization from scratch, and (iii) to avoid considering unproductive uses for extra resources. To meet these challenges, this paper presents three types of locally optimal algorithms: link analysis, local reoptimization and local constraint propagation. These algorithms are d...

• Type: Conference
• Year: 2009
• Where: ATAL
• Authors: Emma Bowring, Zhengyu Yin, Rob Zinkov, Milind Tambe
• Keywords: Artificial Intelligence, Artificial Intelligence, ATAL 2009, Resource Constraints, Sensitivity Analysis