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Distributing Coalitional Value Calculations Among Cooperating Agents

Distributing Coalitional Value Calculations Among Cooperating Agents
Distributing Coalitional Value Calculations Among Cooperating Agents
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, since the number of possible coalitions increases exponentially with the number of agents involved, having one agent calculate all the values is inefficient. 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, and has minimal memory requirements. To evaluate the effectiveness of our algorithm we compare it with the only other algorithm available in the literature (due to Shehory and Kraus). This shows that for the case of 25 agents, the distribution process of our algorithm took 0.00037% of the time, the values were calculated using 0.000006% of the memory, the calculation redundancy was reduced from 477826101 to 0, and the total number of bytes sent between the agents dropped from 674047872 to 0 (note that for larger numbers of agents, these improvements become exponentially better).
152-157
Rahwan, T.
476029f3-5484-4747-9f44-f63f3687083c
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Rahwan, T.
476029f3-5484-4747-9f44-f63f3687083c
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Rahwan, T. and Jennings, N. R. (2005) Distributing Coalitional Value Calculations Among Cooperating Agents. 25th National Conference on AI (AAAI), United States. pp. 152-157 .

Record type: Conference or Workshop Item (Paper)

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, since the number of possible coalitions increases exponentially with the number of agents involved, having one agent calculate all the values is inefficient. 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, and has minimal memory requirements. To evaluate the effectiveness of our algorithm we compare it with the only other algorithm available in the literature (due to Shehory and Kraus). This shows that for the case of 25 agents, the distribution process of our algorithm took 0.00037% of the time, the values were calculated using 0.000006% of the memory, the calculation redundancy was reduced from 477826101 to 0, and the total number of bytes sent between the agents dropped from 674047872 to 0 (note that for larger numbers of agents, these improvements become exponentially better).

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Published date: 2005
Venue - Dates: 25th National Conference on AI (AAAI), United States, 2005-01-01
Organisations: Agents, Interactions & Complexity

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Local EPrints ID: 261139
URI: http://eprints.soton.ac.uk/id/eprint/261139
PURE UUID: b6fdbf5d-f46c-4fcb-bfcc-ebae181d8c16

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Date deposited: 10 Aug 2005
Last modified: 16 Dec 2019 20:44

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