Bounded Decentralised Coordination over Multiple Objectives

Delle Fave, Francesco Maria, Stranders, Ruben, Rogers, Alex and Jennings, Nick (2011) Bounded Decentralised Coordination over Multiple Objectives. In, The Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Taipei, Taiwan, 02 - 06 May 2011. International Foundation for Autonomous Agents and Multiagent Systems, 371-378.


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We propose the bounded multi-objective max-sum algorithm (B-MOMS), the first decentralised coordination algorithm for multi-objective optimisation problems. B-MOMS extends the max-sum message-passing algorithm for decentralised coordination to compute bounded approximate solutions to multi-objective decentralised constraint optimisation problems (MO-DCOPs). Specifically, we prove the optimality of B-MOMS in acyclic constraint graphs, and derive problem dependent bounds on its approximation ratio when these graphs contain cycles. Furthermore, we empirically evaluate its performance on a multi-objective extension of the canonical graph colouring problem. In so doing, we demonstrate that, for the settings we consider, the approximation ratio never exceeds 2, and is typically less than 1.5 for less-constrained graphs. Moreover, the runtime required by B-MOMS on the problem instances we considered never exceeds 30 minutes, even for maximally constrained graphs with $100$ agents. Thus, B-MOMS brings the problem of multi-objective optimisation well within the boundaries of the limited capabilities of embedded agents.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: 2-6 May 2011
ISBNs: 0982657153 (electronic)
9780982657157 (electronic)
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Agents, Interactions & Complexity
ePrint ID: 271958
Date Deposited: 28 Jan 2011 12:00
Last Modified: 14 Apr 2014 11:34
Research Funder: EPSRC
Funded by: EPSRC (EP/I011587/1)
Led by: Nick Jennings
1 January 2011 to 31 December 2015
Publisher: International Foundation for Autonomous Agents and Multiagent Systems
Further Information:Google Scholar

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