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ModuleInformation

CSC3006

Artificial Intelligence

Course Contents

Module introduction:

  • artificial intelligence - definition, scope, successes and limitations.
  • Logic, propositional calculus, predicate calculus, inference; fuzzy logic; logical programming, PROLOG.
  • Expert Systems, knowledge, domains, rules, inference engine, forward and backward chaining, tree searching, probability and certainty, combining fuzzy facts, apriori probability, applications.
  • Information retrieval and disambiguation.
  • Introduction to pattern recognition and neural networks.
  • Linguistics, grammar, surface structure, deep structure, structure representations, transformations, lexical decomposition, n-gram models, classification, domains.
  • Speech recognition.

Supplementary Notes

None

Learning Outcomes

  • Knowledge and understanding of techniques and selected software relevant to the field of artificial intelligence. 
  • Ability to identify techniques relevant to particular problems in artificial intelligence.
  • Ability to discuss and provide proofs for basic rules used in artificial intelligence. 
  • Ability to identify opportunities for software solutions. 
  • Ability to interrogate a knowledge base in PROLOG. 
  • Ability to understand and use natural language grammars. 
  • Ability to solve specific problems using the rules of artificial intelligence e.g. in pattern recognition.

Skills

Analysis of problems, design of solutions, application of techniques, understanding results.