Group thinking support with multiple agents

Nishimoto, Katsutaro; Sumi, Y.; Kadobayashi, Rieko; Mase, Kenji; Nakatsu, Ryohei

doi:10.1002/(sici)1520-684x(199812)29:14<21::aid-scj3>3.0.co;2-s

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Currently, the AI facilitator of our research may simply draw conclusions based on the majority keywords. In the future, the AI facilitators should also consider the lack of consensus, the presence of minority keywords, and the keywords that were mentioned only at the beginning of the discussion [18]. In some cases, the AI facilitator may need to present some new keywords that encourage a change in thinking.…”

Section: Guessing Participant U's Opinions and Intentionsmentioning

confidence: 99%

A Facilitator Support System that Overlooks Keywords Expressing the True Intentions of All Discussion Participants

Oshima¹,

Oyama²,

Sasaki³

et al. 2021

IJACSA

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This paper proposed the Keyword Movement Disclose System (KMDS), which allows a facilitator of discussion to watch a record of the moving keywords in a Discussion Board System (DBS). In the DBS, the discussion participants place each keyword in a box made for each item to be discussed. The keywords in the box were expected to show each participant's opinion and intention, because the participant's individual display was not disclosed to the other participants. Therefore, if the facilitator of the discussion can see the true opinions and intentions of all participants via the keywords in the boxes through the KMDS, the facilitator will be more appropriately advance the discussions and be able to draw conclusions based on diverse opinions. Moreover, the KMDS may contribute to the development of an artificial intelligence facilitator. In this paper, we conducted an experiment in which ten facilitators were asked to listen to a recorded discussion held by nine participants using the DBS. Five of the facilitators used the KMDS while listening the recorded discussion. It was suggested that KMDS may allow the facilitators to build a consensus from various viewpoints of the participants, although the results of the experiment did not show much difference depending on the conditions with/without KMDS.

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Section: Guessing Participant U's Opinions and Intentionsmentioning

confidence: 99%

A Facilitator Support System that Overlooks Keywords Expressing the True Intentions of All Discussion Participants

Oshima¹,

Oyama²,

Sasaki³

et al. 2021

IJACSA

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“…In recent years, demands for systems to effectively support and enhance group activities are rapidly increasing due to growing complexities in society and business as well as diversity in user needs (Nishimoto et al, 1998). However, most of these ordinary systems are not equipped with facilities to support and/or enhance the creativity of a group as one of its functions (Nishimoto et al, 1998). This is also the case for CBR systems.…”

Section: Case-based Reasoningmentioning

confidence: 99%

Integrating web 2.0 with the case‐based reasoning cycle: A systems approach

Means

et al. 2009

Syst. Res.

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Traditional case-based reasoning (CBR) research has focused on the theories and heuristics of case representation, retrieval, reuse, revision and retention, while little attention has been paid to the users of CBR systems. In an effort to facilitate and improve the literature related to the CBR cycle as it relates to users, this paper proposes an extended CBR framework which allows users to play a more active role. The extended framework integrates the classical CBR R4-Cycle approach with Web 2.0 technologies such as blogs and RSS (Really Simple Syndication) feeds. The purpose of the extended CBR 2.0 framework is to encourage and enable users to contribute to case retrieval, case revision, case reuse and case retention. This paper also introduces some ideas to deploy Web 2.0 technologies along with CBR systems, with a discussion of the integration of Web 2.0 and CBR systems in systems perspectives.

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