Abstract
When multiagent simulations are used for consensus building among stakeholders, it is important not only that the domain experts can deeply understand stakeholders' actual behavior but also that the stakeholders can feel the simulation result as their solution. To this end, we propose a modeling methodology which combines several techniques with the participatory method which takes stakeholders into the modeling process using role playing games (RPG). There are two types of model required to simulate a social system as a multiagent system: agents (internal models) and interactions. Hence, we considered a modeling method according to each character. In modeling an agent (e.g. decision making) which is implicit in human, the identification of the model greatly depends on the modeler's ability. Therefore we propose a modeling method wherein classification learning creates an alternative model from RPG log data for validating the domain experts' hypothesis. On the other hand, in modeling interactions (e.g. negotiation) which are emerged outside of human, it is rather important to show and capture continuously appeared interactions. Therefore we propose a modeling method with participatory simulation where a stakeholder participates as an avatar and agents act as the other stakeholders in order to deeply understand the stakeholders' interactions. Our methodology was effective to give the domain experts a deeper understanding through a real case study of agricultural economics in the northeast of Thailand [17].
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems |
| Pages | 81-88 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2006 Dec 1 |
| Externally published | Yes |
| Event | Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS - Hakodate, Japan Duration: 2006 May 8 → 2006 May 12 |
Publication series
| Name | Proceedings of the International Conference on Autonomous Agents |
|---|---|
| Volume | 2006 |
Conference
| Conference | Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS |
|---|---|
| Country | Japan |
| City | Hakodate |
| Period | 06/5/8 → 06/5/12 |
Fingerprint
Keywords
- Design
ASJC Scopus subject areas
- Engineering(all)
Cite this
Modeling agents and interactions in agricultural economics. / Torii, Daisuke; Ishida, Toru; Bousquet, Francois.
Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems. 2006. p. 81-88 (Proceedings of the International Conference on Autonomous Agents; Vol. 2006).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Modeling agents and interactions in agricultural economics
AU - Torii, Daisuke
AU - Ishida, Toru
AU - Bousquet, Francois
PY - 2006/12/1
Y1 - 2006/12/1
N2 - When multiagent simulations are used for consensus building among stakeholders, it is important not only that the domain experts can deeply understand stakeholders' actual behavior but also that the stakeholders can feel the simulation result as their solution. To this end, we propose a modeling methodology which combines several techniques with the participatory method which takes stakeholders into the modeling process using role playing games (RPG). There are two types of model required to simulate a social system as a multiagent system: agents (internal models) and interactions. Hence, we considered a modeling method according to each character. In modeling an agent (e.g. decision making) which is implicit in human, the identification of the model greatly depends on the modeler's ability. Therefore we propose a modeling method wherein classification learning creates an alternative model from RPG log data for validating the domain experts' hypothesis. On the other hand, in modeling interactions (e.g. negotiation) which are emerged outside of human, it is rather important to show and capture continuously appeared interactions. Therefore we propose a modeling method with participatory simulation where a stakeholder participates as an avatar and agents act as the other stakeholders in order to deeply understand the stakeholders' interactions. Our methodology was effective to give the domain experts a deeper understanding through a real case study of agricultural economics in the northeast of Thailand [17].
AB - When multiagent simulations are used for consensus building among stakeholders, it is important not only that the domain experts can deeply understand stakeholders' actual behavior but also that the stakeholders can feel the simulation result as their solution. To this end, we propose a modeling methodology which combines several techniques with the participatory method which takes stakeholders into the modeling process using role playing games (RPG). There are two types of model required to simulate a social system as a multiagent system: agents (internal models) and interactions. Hence, we considered a modeling method according to each character. In modeling an agent (e.g. decision making) which is implicit in human, the identification of the model greatly depends on the modeler's ability. Therefore we propose a modeling method wherein classification learning creates an alternative model from RPG log data for validating the domain experts' hypothesis. On the other hand, in modeling interactions (e.g. negotiation) which are emerged outside of human, it is rather important to show and capture continuously appeared interactions. Therefore we propose a modeling method with participatory simulation where a stakeholder participates as an avatar and agents act as the other stakeholders in order to deeply understand the stakeholders' interactions. Our methodology was effective to give the domain experts a deeper understanding through a real case study of agricultural economics in the northeast of Thailand [17].
KW - Design
UR - http://www.scopus.com/inward/record.url?scp=34247228149&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34247228149&partnerID=8YFLogxK
U2 - 10.1145/1160633.1160643
DO - 10.1145/1160633.1160643
M3 - Conference contribution
AN - SCOPUS:34247228149
SN - 1595933034
SN - 9781595933034
T3 - Proceedings of the International Conference on Autonomous Agents
SP - 81
EP - 88
BT - Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems
ER -