|Module Title||MODEL-BASED REASONING|
|Co-ordinator||Dr Mark Ratcliffe|
|Course delivery||Lecture||20 lectures|
|Workshop||(Up to) 3 workshop sessions|
|Practical||(Up to) 3 x 1 hr sessions|
|Supplementary examination||Will take the same form, under the terms of the Department's policy|
A problem at the heart of the research agenda for artificial intelligence is how to reason about the world. This module assesses the adequacy of models for this domain and aims to give students an understanding of the issues involved in effectively modelling and reasoning about systems. The course will be organised around a number of application domains and will show how the requirements of knowledge and software reuse lead to the need for both compositional models and multiple models of phenomena.
A problem at the heart of the research agenda for artificial intelligence is how to reason about the world. This module assesses the adequacy of models for this domain and aims to give students an understanding of the issues involved in effectively modelling and reasoning about the systems. The course will be organised around a number of application domains and these will be used to focus on specific problems that arise in modelling real systems, to show how existing techniques can be used and where such techniques prove inadequate.
On successful completion of this module students should:
1. Introduction - 1 Week
Revision of material in CS36110
2. QSIM: Its problems and successors - 1 Week
Approaches to the problem of spurious behaviours within constraint based ontology.
3. Fuzzy Qualitative Reasoning - 2 Weeks
FuSim and Mycroft and ongoing developments.
4. Modelling Issues - 2 Weeks
Compositional modelling, model properties, model switching, modelling methodology.
5. Functional Approaches - 1 Week
Reasoning about function, FMEA and functional labels, applications in design and diagnosis.
6. Model-based Diagnosis - 1 Week
Approaches to diagnosis, diagnostic methodology.
7. Learning of Models - 1 Week
Constraint-based learning of model structure from data.
8. Summary and Review - 1 Week
** Recommended Text
B.J. Kuipers. (1994) Qualitative reasoning: modelling and simulation with incomplete knowledge. MIT Press