Name
Abstract | ||
|---|---|---|
Multiuser museum interactives are computer systems installed in museums or galleries which allow several visitors to interact together with digital representations of artefacts and information from the museum's collection. In this paper, we describe WeCurate, a socio-technical system that supports co-browsing across multiple devices and enables groups of users to collaboratively curate a collection of images, through negotiation, collective decision making and voting. The engineering of such a system is challenging since it requires to address several problems such as: distributed workflow control, collective decision making and multiuser synchronous interactions. The system uses a peer-to-peer Electronic Institution (EI) to manage and execute a distributed curation workflow and models community interactions into scenes, where users engage in different social activities. Social interactions are enacted by intelligent agents that interface the users participating in the curation workflow with the EI infrastructure. The multiagent system supports collective decision making, representing the actions of the users within the EI, where the agents advocate and support the desires of their users e.g. aggregating opinions for deciding which images are interesting enough to be discussed, and proposing interactions and resolutions between disagreeing group members. Throughout the paper, we describe the enabling technologies of WeCurate, the peer-to-peer EI infrastructure, the agent collective decision making capabilities and the multi-modal interface. We present a system evaluation based on data collected from cultural exhibitions in which WeCurate was used as supporting multiuser interactive. HighlightsWe describe a socio-technical system, supporting co-browsing across multiple devices.The system supports collective decision making based on argumentation and negotiation.Electronic institutions model social interactions, enacted by intelligent agents.We evaluate the social awareness perceived by the users.We evaluate the collective decision models employed by the agents. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.engappai.2015.08.013 | Engineering Applications of Artificial Intelligence |
Keywords | Field | DocType |
Distributed artificial intelligence,Collective decision making,Argumentation,Negotiation | Intelligent agent,Computer science,Social consciousness,Argumentation theory,Exhibition,Artificial intelligence,R-CAST,Workflow,Machine learning,Group decision-making,Negotiation | Journal |
Volume | Issue | ISSN |
46 | PA | 0952-1976 |
Citations | PageRank | References |
0 | 0.34 | 36 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Confalonieri | 1 | 144 | 26.90 |
| Matthew Yee-King | 2 | 28 | 9.73 |
| Katina Hazelden | 3 | 14 | 3.37 |
| Mark D'inverno | 4 | 1195 | 116.29 |
| Dave de Jonge | 5 | 26 | 8.04 |
| Nardine Osman | 6 | 69 | 14.54 |
| Carles Sierra | 7 | 5101 | 454.99 |
| Leila Amgoud | 8 | 2560 | 151.43 |
| Henri Prade | 9 | 10549 | 1445.02 |