Logic, Ontology, and Knowledge Representation - 2019 entry

Knowledge representation, the codification of knowledge and reasoning in a form that is amenable to computational manipulation, is a fundamental requirement for the application of Artificial Intelligence to real-world problems. The study of knowledge representation Is particularly fascinating as it combines technical issues concerning the digital representation and manipulation of knowledge with ontological issues concerned with the nature and structure of human knowledge and understanding of the world. Bridging the gap between these two aspects are formal languages or logics that can be used for expressing knowledge in a form that can be handled by computers. This module will provide an introduction to all these aspects, building on an assumed prior acquaintance with computer data structures and elementary formal logic.
 

PRE-REQUISITE MODULES ECM2418 Computer Languages and Representations (specifically the part relating to formal logic)

An important goal of Artificial Intelligence is to explore ways of endowing machines with the knowledge and reasoning capacities to enable them to behave in ways which we might recognise as intelligent. Of particular concern is the drive to emulate human ‘common-sense’ understanding, which requires the assimilation of a vast range of mundane facts, many of them seemingly trivial, on the basis of which we are able to conduct our day-to-day negotiations with the world and with each other. This enterprise requires us to answer such questions as: How do we describe and classify the elements that make up our common-sense knowledge of the world? How are all these elements interrelated? What methods can we use to reason effectively about our knowledge in order to derive new conclusions from existing facts? In this module you will be introduced to some of the main bodies of theory which have been employed to help answer these questions in the context of modern computer technology, and will see their uses illustrated in a number of application case studies

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

Discipline Specific Skills and Knowledge

Personal and Key Transferable / Employment Skills and Knowledge

• Introduction and overview: What is logic? What is ontology? What is knowledge representation?
• Historical development of knowledge representation in the context of Artificial Intelligence
• Recapitulation of elementary propositional and first-order logic; properties of logical systems including soundness, completeness, expressivity, and tractability; introduction to further logics such as modal logic, default logic, and description logic.
• Representations of common-sense knowledge
• Historical introduction to ontology, from ancient philosophy to the semantic web
• Fundamental principles of formal ontology: classes and instances, taxonomies and partonomies, dependence and independence.
• Examples of modern formal ontologies, including upper ontologies and domain ontologies.
• Knowledge Representation and Ontology case studies (details may vary from year to year; typical topics include space and time, causality, agents and roles, parts and wholes).

All re-assessment will be by a single written exercise. For referred candidates the mark will be capped at 50%. For deferred candidates, depending on circumstances, deferral may be possible in one or two of the original pieces of coursework.

Basic reading:

ELE: http://vle.exeter.ac.uk/

Web based and Electronic Resources:

Other Resources:

Reading list for this module: