Trust-Based Mechanism Design
Trust-Based Mechanism Design
We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.
748-755
Dash, R. K .
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Ramchurn, S.D.
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Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
2004
Dash, R. K .
d5ece5a7-1b4d-494b-9a6a-6146fe701aab
Ramchurn, S.D.
1d62ae2a-a498-444e-912d-a6082d3aaea3
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Dash, R. K ., Ramchurn, S.D. and Jennings, N. R.
(2004)
Trust-Based Mechanism Design.
3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems, New York, United States.
19 - 23 Jul 2004.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
We define trust-based mechanism design as an augmentation of traditional mechanism design in which agents take into account the degree of trust that they have in their counterparts when determining their allocations. To this end, we develop an efficient, individually rational, and incentive compatible mechanism based on trust. This mechanism is embedded in a task allocation scenario in which the trust in an agent is derived from the reported performance success of that agent by all the other agents in the system. We also empirically study the evolution of our mechanism when iterated and show that, in the long run, it always chooses the most successful and cheapest agents to fulfill an allocation and chooses better allocations than other comparable models when faced with biased reporting.
More information
Published date: 2004
Additional Information:
Event Dates: 19-23 July 2004
Venue - Dates:
3rd Int. Conf. on Autonomous Agents and Multi-Agent Systems, New York, United States, 2004-07-19 - 2004-07-23
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 259352
URI: http://eprints.soton.ac.uk/id/eprint/259352
PURE UUID: 683b62f7-e952-4b4a-968e-89f26ba045ff
Catalogue record
Date deposited: 06 Sep 2004
Last modified: 15 Mar 2024 03:22
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Contributors
Author:
R. K . Dash
Author:
S.D. Ramchurn
Author:
N. R. Jennings
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