Name
Abstract | ||
|---|---|---|
Recently, many universities, particularly in China, started to offer undergraduate degree programs for the discipline of "Intelligence Science and Technology". However, until now, there is no universally recognized, explicitly defined, standard curriculum for the discipline of "Intelligence Science and Technology". This is probably because it is very difficult for scientists from various disciplines (including Computer Science, Artificial Intelligence, Cognitive Science, etc.) to reach a universally accepted answer to the fundamental question, what is intelligence and why study it? Based on our understanding and consideration about the discipline of "Intelligence Science and Technology", in this paper we sketch a primary framework for the body of knowledge about the discipline of "Intelligence Science and Technology", propose a curriculum model for undergraduate degree programs of the discipline, and show example curriculums. Many practical curriculums for the discipline of "Intelligence Science and Technology" can be derived and developed from our curriculum model according to different emphases on a specific scientific or technical aspect in different departments. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SmartWorld.2018.00075 | 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) |
Keywords | Field | DocType |
intelligence, biological and/or organism intelligence, artificial intelligence, undergraduate curriculum model, general education | Body of knowledge,Computer science,Engineering ethics,Curriculum,General education,Sketch,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-5386-9381-0 | 0 | 0.34 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingde Cheng | 1 | 542 | 85.38 |
| Runhe Huang | 2 | 407 | 56.46 |
| Jin, Q. | 3 | 233 | 33.40 |
| Jianhua Ma | 4 | 1401 | 148.82 |
| Yi Pan | 5 | 9 | 3.61 |