Optimizing agent-based meeting scheduling through preference estimation

Chun, Hon Wai; Wai, Hon; Wong, Rosa S.

doi:10.1016/j.engappai.2003.09.009

Cited by 37 publications

(19 citation statements)

References 21 publications

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“…[24]). Several systems implement different approaches [22,59]. Although meeting schedulers were not conceived to support DCoPs, they can help such communities be more efficient.…”

Section: Descriptions Of the Systemsmentioning

confidence: 99%

“…In the Synchronous Interactions category, we identified five major Conversational Agent for IM AINI [39] Meeting Scheduling [22] [ 59,60] RESCH [62] MSRAC [8] [89]…”

Section: Synchronous Interactionsmentioning

confidence: 99%

“…Lee et al [60] refine Lee and Pan's system by using ontologies. Another system for scheduling meetings is proposed by Chun et al [22]. The system is able to define participants' preferences by observing the negotiation involved in the meeting organization.…”

Section: Descriptions Of the Systemsmentioning

confidence: 99%

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Agent and multi-agent applications to support distributed communities of practice: a short review

Sato

Azevedo

Barthès

2011

Auton Agent Multi-Agent Syst

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This paper concerns the relationship between agents or multi-agent systems and distributed communities of practice. It presents a review of a number of agent and multiagent applications with features that could contribute to supporting distributed communities of practice. The association is promising because of features like autonomy, pro-activity, flexibility or ability to integrate systems that characterize agents and multi-agent systems. Furthermore, such an association is a step towards building mixed communities of humans and artificial agents. To understand how agents and multi-agent systems could answer some of the needs of distributed communities of practice, we organize the analyzed applications into five different categories defined by considering the main activities of a community, namely: Individual Participation, Synchronous Interactions, Asynchronous Interactions, Publishing and Community Cultivation. Such a classification helps us identify the relevant features of the current technology and determine some that should be further developed, e.g. to support community coordination or gather information related to virtual communities. For each application we selected, we present its main approach and point out its potential interest.

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“…[24]). Several systems implement different approaches [22,59]. Although meeting schedulers were not conceived to support DCoPs, they can help such communities be more efficient.…”

Section: Descriptions Of the Systemsmentioning

confidence: 99%

“…In the Synchronous Interactions category, we identified five major Conversational Agent for IM AINI [39] Meeting Scheduling [22] [ 59,60] RESCH [62] MSRAC [8] [89]…”

Section: Synchronous Interactionsmentioning

confidence: 99%

See 1 more Smart Citation

Agent and multi-agent applications to support distributed communities of practice: a short review

Sato

Azevedo

Barthès

2011

Auton Agent Multi-Agent Syst

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“…Minor participants can attend a meeting, where users classified as Info will only receive an information about a meeting after the meeting is accepted by every participant. This classification is extending the classification of [4] with the superordinate instance of Very important attendees and the Info classification for users not participating the meeting, but want to be informed about when the meeting will occur.…”

Section: Types Of Agentsmentioning

confidence: 99%

“…Chun et al introduced an agent-based negotiation algorithm within an environment they called "Mobile Agents for Office Automation" (MAFOA) [4] using two types of agents: a secretary and a meeting agent.…”

Section: Related Workmentioning

confidence: 99%

Agent-based meeting scheduling support using mobile clients

Niederer

Strobel

2009

2009 Second International Conference on the Applications of Digital Information and Web Technologies

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In this paper, we present a distributed multi-agent meeting scheduling system for mobile devices. This mobile agent system supports people on the move to locate feasible time slots to meet with each other, using their mobile devices. It negotiates the best suitable times integrating timetables and time preferences from the participants. Unlike to current approaches, the negotiation of the meeting time is fully executed on mobile devices. As mobile devices are limited in resources, the introduced protocol additionally allows, to outsource the main part of the negotiation to a self-contained scheduling service.

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A Fuzzy Negotiation Model with Genetic Algorithms

Zhai

Yuying

et al.

IFIP — The International Federation for Information Processing

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Optimizing agent-based meeting scheduling through preference estimation

Cited by 37 publications

References 21 publications

Agent and multi-agent applications to support distributed communities of practice: a short review

Agent and multi-agent applications to support distributed communities of practice: a short review

Agent-based meeting scheduling support using mobile clients

A Fuzzy Negotiation Model with Genetic Algorithms

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