Name
Abstract | ||
|---|---|---|
One of the technical challenges in the knowledge society is to build a situated intelligent agent that can join our knowledge process to learn and exploit tacit knowledge in a situated fashion. Social intelligence design sheds light on the social context in which agents might take part in our knowledge process where tacit knowledge comes into play. We aim at building a computational framework for understanding and augmenting social intelligence that is defined as the ability of an agent to build a social relationship with others and to use it when solving a variety of problems, and the ability of a group to learn from experience when solving problems. In this paper, I outline a conceptual framework of social intelligence design at three scales ranging from the micro to the macro. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GrC.2010.170 | GrC |
Keywords | Field | DocType |
knowledge process,conceptual framework,computational framework,social intelligence,social context,tacit knowledge,social relationship,social intelligence design,shared situated intelligence,social intelligence design shed,knowledge society,knowledge engineering,speech,software agents,collaboration,artificial intelligence,intelligent agent | Situated,Intelligent agent,Marketing and artificial intelligence,Computer science,Knowledge management,Knowledge engineering,Social intelligence,Intelligence cycle (target-centric approach),Artificial intelligence, situated approach,Tacit knowledge | Conference |
Citations | PageRank | References |
2 | 0.39 | 1 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Toyoaki Nishida | 1 | 1097 | 196.19 |