Artificial Intelligence

Knowledge Representation is at the heart of the great challenge of Artificial Intelligence: to understand the nature of intelligence and cognition so that computers can exhibit human-like abilities. Pioneers of the field such as John McCarthy believed that (artificial) intelligence could be formalised as symbolic reasoning with explicit representations of human knowledge given in some form of Logic.  In this setting, the key challenge is to effectively represent knowledge in computers and to exploit it algorithmically to perform tasks in an intelligent way. Since its very inception, Knowledge Representation has been an inter-disciplinary field which lies at the intersection between Logic and Metamathematics, Philosophy, and Computer Science. This course focuses on general methods for representing human knowledge in Artificial Intelligence, and will be given mostly from a Computer Science perspective. The course will cover not only foundations and algorithms, but also Semantic and Ontology-based Technologies and their role on modern Information Systems.