Knowledge Engineering for Intelligent Decision Support

Knowledge Engineering for Intelligent Decision Support

María Vanina Martínez

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Early Career. Pages 5131-5135. https://doi.org/10.24963/ijcai.2017/736

Knowledge can be seen as the collection of skills and information an individual (or group) has acquired through experience, while intelligence as the ability to apply such knowledge. In many areas of Artificial Intelligence, we have been focusing for the last 40 years on the formalization and development of automated ways of finding and collecting data, as well as on the construction of models to represent that data adequately in a way that an automated system can make sense of it. However, in order to achieve real artificial intelligence we need to go beyond data and knowledge representation, and deeper into how such a system could, and would, use available knowledge in order to empower and enhance the capabilities of humans in making decisions in real-world applications. From my point of view, an AI should be able to combine automatically acquired data and knowledge together with specific domain expertise from the users that the tool is expected to help.
Keywords:
Knowledge Representation, Reasoning, and Logic: Reasoning about Knowlege and Belief
Knowledge Representation, Reasoning, and Logic: Non-monotonic Reasoning
Uncertainty in AI: Uncertainty in AI
Multidisciplinary Topics and Applications: Intelligent Database Systems