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An improved dynamic programming algorithm for coalition structure generation

An improved dynamic programming algorithm for coalition structure generation
An improved dynamic programming algorithm for coalition structure generation
Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of partitioning the set of agents into exhaustive and disjoint coalitions so as to maximize social welfare. This coalition structure generation problem is extremely challenging due to the exponential number of partitions that need to be examined. Specifically, given n agents, there are O(nn) possible partitions. To date, the only algorithm that can find an optimal solution in O(3n) is the Dynamic Programming (DP) algorithm, due To Rothkopf et al. However, one of the main limitations of DP is that it requires a significant amount of memory. In this paper, we devise an Improved Dynamic Programming algorithm (IDP) that is proven to perform fewer operations than DP (e.g. 38.7% of the operations given 25 agents), and is shown to use only 33.3% of the memory in the best case, and 66.6% in the worst.
1417-1420
Rahwan, Talal
476029f3-5484-4747-9f44-f63f3687083c
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Rahwan, Talal
476029f3-5484-4747-9f44-f63f3687083c
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Rahwan, Talal and Jennings, N. R. (2008) An improved dynamic programming algorithm for coalition structure generation. Proc 7th Int Conf on Autonomous Agents and Multi-Agent Systems, Estoril, Portugal. pp. 1417-1420 .

Record type: Conference or Workshop Item (Paper)

Abstract

Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of partitioning the set of agents into exhaustive and disjoint coalitions so as to maximize social welfare. This coalition structure generation problem is extremely challenging due to the exponential number of partitions that need to be examined. Specifically, given n agents, there are O(nn) possible partitions. To date, the only algorithm that can find an optimal solution in O(3n) is the Dynamic Programming (DP) algorithm, due To Rothkopf et al. However, one of the main limitations of DP is that it requires a significant amount of memory. In this paper, we devise an Improved Dynamic Programming algorithm (IDP) that is proven to perform fewer operations than DP (e.g. 38.7% of the operations given 25 agents), and is shown to use only 33.3% of the memory in the best case, and 66.6% in the worst.

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Published date: 2008
Venue - Dates: Proc 7th Int Conf on Autonomous Agents and Multi-Agent Systems, Estoril, Portugal, 2008-01-01
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 265062
URI: http://eprints.soton.ac.uk/id/eprint/265062
PURE UUID: b14fc95d-5500-4315-abf2-43c906a0b773

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Date deposited: 21 Jan 2008 15:14
Last modified: 14 Mar 2024 08:02

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Contributors

Author: Talal Rahwan
Author: N. R. Jennings

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