Faculty of Science

Objectives

To expose students to the facility of, and advances in, Knowledge Engineering (KE) with focus on knowledge processing and building of intelligent problem solvers.

Contents

Overview of past, current and future trends in Artificial Intelligence (AI); computational models of knowledge; Knowledge acquisition and machine learning; Distributed AI; Qualitative reasoning, uncertainty management in AI; Bayesian networks; Analogical reasoning; Game theory, case-based reasoning; Ontology engineering, organisational process models; Intelligent Tutoring Systems; Client-server and distributed object computing, multi-layer knowledge bases; Computational models of knowledge; functional reasoning, explanations and analysis. Current research and advances in KE.