### Abstract

The process of forming coalitions of software agents generally requires calculating a value for every possible coalition which indicates how beneficial that coalition would be if it was formed. Now, instead of having a single agent calculate all these values (as is typically the case), it is more efficient to distribute this calculation among the agents, thus using all the computational resources available to the system and avoiding the existence of a single point of failure. Given this, we present a novel algorithm for distributing this calculation among agents in cooperative environments. Specifically, by using our algorithm, each agent is assigned some part of the calculation such that the agents' shares are exhaustive and disjoint. Moreover, the algorithm is decentralized, requires no communication between the agents, has minimal memory requirements, and can reflect variations in the computational speeds of the agents. To evaluate the effectiveness of our algorithm, we compare it with the only other algorithm available in the literature for distributing the coalitional value calculations (due to Shehory and Kraus). This shows that for the case of 25 agents, the distribution process of our algorithm took less than 0.02% of the time, the values were calculated using 0.000006% of the memory, the calculation redundancy was reduced from 383229848 to 0, and the total number of bytes sent between the agents dropped from 1146989648 to 0 (note that for larger numbers of agents, these improvements become exponentially better).

Original language | English (US) |
---|---|

Pages (from-to) | 535-567 |

Number of pages | 33 |

Journal | Artificial Intelligence |

Volume | 171 |

Issue number | 8-9 |

DOIs | |

State | Published - Jun 1 2007 |

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### Keywords

- Coalition formation
- Multi-agent systems

### ASJC Scopus subject areas

- Artificial Intelligence
- Computational Theory and Mathematics

### Cite this

*Artificial Intelligence*,

*171*(8-9), 535-567. https://doi.org/10.1016/j.artint.2007.03.002

**An algorithm for distributing coalitional value calculations among cooperating agents.** / Rahwan, Talal; Jennings, Nicholas R.

Research output: Contribution to journal › Article

*Artificial Intelligence*, vol. 171, no. 8-9, pp. 535-567. https://doi.org/10.1016/j.artint.2007.03.002

}

TY - JOUR

T1 - An algorithm for distributing coalitional value calculations among cooperating agents

AU - Rahwan, Talal

AU - Jennings, Nicholas R.

PY - 2007/6/1

Y1 - 2007/6/1

N2 - The process of forming coalitions of software agents generally requires calculating a value for every possible coalition which indicates how beneficial that coalition would be if it was formed. Now, instead of having a single agent calculate all these values (as is typically the case), it is more efficient to distribute this calculation among the agents, thus using all the computational resources available to the system and avoiding the existence of a single point of failure. Given this, we present a novel algorithm for distributing this calculation among agents in cooperative environments. Specifically, by using our algorithm, each agent is assigned some part of the calculation such that the agents' shares are exhaustive and disjoint. Moreover, the algorithm is decentralized, requires no communication between the agents, has minimal memory requirements, and can reflect variations in the computational speeds of the agents. To evaluate the effectiveness of our algorithm, we compare it with the only other algorithm available in the literature for distributing the coalitional value calculations (due to Shehory and Kraus). This shows that for the case of 25 agents, the distribution process of our algorithm took less than 0.02% of the time, the values were calculated using 0.000006% of the memory, the calculation redundancy was reduced from 383229848 to 0, and the total number of bytes sent between the agents dropped from 1146989648 to 0 (note that for larger numbers of agents, these improvements become exponentially better).

AB - The process of forming coalitions of software agents generally requires calculating a value for every possible coalition which indicates how beneficial that coalition would be if it was formed. Now, instead of having a single agent calculate all these values (as is typically the case), it is more efficient to distribute this calculation among the agents, thus using all the computational resources available to the system and avoiding the existence of a single point of failure. Given this, we present a novel algorithm for distributing this calculation among agents in cooperative environments. Specifically, by using our algorithm, each agent is assigned some part of the calculation such that the agents' shares are exhaustive and disjoint. Moreover, the algorithm is decentralized, requires no communication between the agents, has minimal memory requirements, and can reflect variations in the computational speeds of the agents. To evaluate the effectiveness of our algorithm, we compare it with the only other algorithm available in the literature for distributing the coalitional value calculations (due to Shehory and Kraus). This shows that for the case of 25 agents, the distribution process of our algorithm took less than 0.02% of the time, the values were calculated using 0.000006% of the memory, the calculation redundancy was reduced from 383229848 to 0, and the total number of bytes sent between the agents dropped from 1146989648 to 0 (note that for larger numbers of agents, these improvements become exponentially better).

KW - Coalition formation

KW - Multi-agent systems

UR - http://www.scopus.com/inward/record.url?scp=34249661503&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34249661503&partnerID=8YFLogxK

U2 - 10.1016/j.artint.2007.03.002

DO - 10.1016/j.artint.2007.03.002

M3 - Article

AN - SCOPUS:34249661503

VL - 171

SP - 535

EP - 567

JO - Artificial Intelligence

JF - Artificial Intelligence

SN - 0004-3702

IS - 8-9

ER -