Using Joint Responsibility to Coordinate Collaborative Problem Solving in Dynamic Environments
Using Joint Responsibility to Coordinate Collaborative Problem Solving in Dynamic Environments
Joint responsibility is a new meta-level description of how cooperating agents should behave when engaged in collaborative problem solving. It is dependent of any specific planning or consensus forming mechanism, but can be mapped down to such a level. An application of the framework to the real world problem of electricity transportation management is given and its implementation is discussed. A comparative analysis of responsibility and two other group organisational structures, selfish problem solvers and communities in which collaborative behaviour emerges from interactions, is undertaken. The aim being to evaluate their relative performance characteristics in dynamic and unpredictable environments in which decisions are taken using partial, imprecise views of the system.
269-275
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Mamdani, E. H.
b590b192-a2bd-4717-9734-5266f43bf08e
1992
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Mamdani, E. H.
b590b192-a2bd-4717-9734-5266f43bf08e
Jennings, N. R. and Mamdani, E. H.
(1992)
Using Joint Responsibility to Coordinate Collaborative Problem Solving in Dynamic Environments.
10th National Conf. on Artificial Intelligence (AAAI-92), San Jose, California, United States.
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Conference or Workshop Item
(Paper)
Abstract
Joint responsibility is a new meta-level description of how cooperating agents should behave when engaged in collaborative problem solving. It is dependent of any specific planning or consensus forming mechanism, but can be mapped down to such a level. An application of the framework to the real world problem of electricity transportation management is given and its implementation is discussed. A comparative analysis of responsibility and two other group organisational structures, selfish problem solvers and communities in which collaborative behaviour emerges from interactions, is undertaken. The aim being to evaluate their relative performance characteristics in dynamic and unpredictable environments in which decisions are taken using partial, imprecise views of the system.
More information
Published date: 1992
Venue - Dates:
10th National Conf. on Artificial Intelligence (AAAI-92), San Jose, California, United States, 1992-01-01
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 252131
URI: http://eprints.soton.ac.uk/id/eprint/252131
PURE UUID: ebcc8e27-d20d-45d7-981f-d7cc3123b4ee
Catalogue record
Date deposited: 05 Dec 2002
Last modified: 14 Mar 2024 05:16
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Contributors
Author:
N. R. Jennings
Author:
E. H. Mamdani
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