IEICE TRANSACTIONS on Information
Designing Multi-Agent Systems Based on Pairwise Agent Interactions
Summary :
Systems comprised of multiple interacting mobile agents provide an alternate network computing paradigm that integrates remote data access, message exchange and migration; which up until now have largely been considered independently. On the surface distributed systems design could be helped by a complete specification of the different interaction patterns, however the number of possible designs in any large scale system undergoes a combinatorial explosion. As a consequence this paper focuses on basic one-to-one agent interactions, or paradigms, which can be used as building blocks; allowing larger system characteristics and performance to be understood in terms of their combination. This paper defines three basic agent paradigms and presents associated performance models. The paradigms are evaluated quantitatively in terms of network traffic, overall processing time and size of memory used, in the context of a distributed DB system developed using the Bee-gent Agent Framework. Comparison of the results and models illustrates the performance trade-off for each paradigm, which are not represented in the models, and some implementation issues of agent frameworks. The paper ends with a case study of how to select an appropriate paradigm.
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- IEICE TRANSACTIONS on Information Vol.E84-D No.8 pp.968-980
- Publication Date
- 2001/08/01
- Publicized
- Online ISSN
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- Type of Manuscript
- Special Section PAPER (Special Issue on Software Agent and Its Applications)
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Takahiro KAWAMURA, Sam JOSEPH, Akihiko OHSUGA, Shinichi HONIDEN, "Designing Multi-Agent Systems Based on Pairwise Agent Interactions" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 8, pp. 968-980, August 2001, doi: .
Abstract: Systems comprised of multiple interacting mobile agents provide an alternate network computing paradigm that integrates remote data access, message exchange and migration; which up until now have largely been considered independently. On the surface distributed systems design could be helped by a complete specification of the different interaction patterns, however the number of possible designs in any large scale system undergoes a combinatorial explosion. As a consequence this paper focuses on basic one-to-one agent interactions, or paradigms, which can be used as building blocks; allowing larger system characteristics and performance to be understood in terms of their combination. This paper defines three basic agent paradigms and presents associated performance models. The paradigms are evaluated quantitatively in terms of network traffic, overall processing time and size of memory used, in the context of a distributed DB system developed using the Bee-gent Agent Framework. Comparison of the results and models illustrates the performance trade-off for each paradigm, which are not represented in the models, and some implementation issues of agent frameworks. The paper ends with a case study of how to select an appropriate paradigm.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_8_968/_p
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@ARTICLE{e84-d_8_968,
author={Takahiro KAWAMURA, Sam JOSEPH, Akihiko OHSUGA, Shinichi HONIDEN, },
journal={IEICE TRANSACTIONS on Information},
title={Designing Multi-Agent Systems Based on Pairwise Agent Interactions},
year={2001},
volume={E84-D},
number={8},
pages={968-980},
abstract={Systems comprised of multiple interacting mobile agents provide an alternate network computing paradigm that integrates remote data access, message exchange and migration; which up until now have largely been considered independently. On the surface distributed systems design could be helped by a complete specification of the different interaction patterns, however the number of possible designs in any large scale system undergoes a combinatorial explosion. As a consequence this paper focuses on basic one-to-one agent interactions, or paradigms, which can be used as building blocks; allowing larger system characteristics and performance to be understood in terms of their combination. This paper defines three basic agent paradigms and presents associated performance models. The paradigms are evaluated quantitatively in terms of network traffic, overall processing time and size of memory used, in the context of a distributed DB system developed using the Bee-gent Agent Framework. Comparison of the results and models illustrates the performance trade-off for each paradigm, which are not represented in the models, and some implementation issues of agent frameworks. The paper ends with a case study of how to select an appropriate paradigm.},
keywords={},
doi={},
ISSN={},
month={August},}
Copy
TY - JOUR
TI - Designing Multi-Agent Systems Based on Pairwise Agent Interactions
T2 - IEICE TRANSACTIONS on Information
SP - 968
EP - 980
AU - Takahiro KAWAMURA
AU - Sam JOSEPH
AU - Akihiko OHSUGA
AU - Shinichi HONIDEN
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2001
AB - Systems comprised of multiple interacting mobile agents provide an alternate network computing paradigm that integrates remote data access, message exchange and migration; which up until now have largely been considered independently. On the surface distributed systems design could be helped by a complete specification of the different interaction patterns, however the number of possible designs in any large scale system undergoes a combinatorial explosion. As a consequence this paper focuses on basic one-to-one agent interactions, or paradigms, which can be used as building blocks; allowing larger system characteristics and performance to be understood in terms of their combination. This paper defines three basic agent paradigms and presents associated performance models. The paradigms are evaluated quantitatively in terms of network traffic, overall processing time and size of memory used, in the context of a distributed DB system developed using the Bee-gent Agent Framework. Comparison of the results and models illustrates the performance trade-off for each paradigm, which are not represented in the models, and some implementation issues of agent frameworks. The paper ends with a case study of how to select an appropriate paradigm.
ER -
English
