NOTE: This web page describes a 10-credit module that was taught between 2005 and 2007. Maybe instead you are looking for CS4618 Artificial Intelligence I or CS4619 Artificial Intelligence II.
- Teaching Materials
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- Context
This 10-credit elective was taught twice between 2005 and 2007 to final-year undergraduates on the main B.Sc. computing degrees in UCC's Computer Science Department.
- Workload
The workload is 6 hours per week for the whole year, and is divided roughly as follows:
- Lectures: 2 lectures per week, each lasting 1 hour.
- Private study: At least 4 hours of private study per week.
- Prerequisites
CS3315: Introduction to Artificial Intelligence.
It is more important, however, for students to have a knowledge of the following:
- Essential: sets; graphs; propositional logic
- Very helpful: functions; relations; probability; predicate logic; programming
- Mildly useful: algorithm complexity; calculus
- Assessment
- Written exam: A three-hour paper in the Summer term.
- Year's work: There will be exercises to be tackled, and these will be essential if students are to master the skills needed for the written exam. However, they will not count towards the overall mark.
- Description
The course will introduce students to the design and construction of intelligent software agents.
The approach will be to start with the simplest reactive agents, and show how to add ever more functionality.
The topics to be covered will include: classification; naive Bayes classifiers; kNN; rules; neural nets; table-driven agents; production systems; genetic algorithms; reinforcement learning; fuzzy logic and fuzzy control; artificial life; ant algorithms; logics for knowledge representation & reasoning; AI search; case-based reasoning; AI planning; multi-agent systems; and natural language processing.
- Aims
- Students should obtain a broad overview of modern AI (including a sense of its successes & failures; a sense of what is easy to do & difficult to do; a sense of its theory & its applications; and a sense of where it is heading).
- They should obtain an in-depth knowledge of core AI techniques, sufficient to enable them to implement their own simple AI systems and sufficient to enable them to critically judge systems they come across that purport to use AI techniques.