Aims:
- To introduce the fundamental concepts and techniques of AI, including planning, search and knowledge representation
- To introduce the scope, subfields and applications of AI, topics to be taken from a list including natural language processing, expert systems, robots and autonomous agents, machine learning and neural networks, and vision.
- To develop skills in AI programming in an appropriate language
Detailed Information
Pre-requisites: none.
Location: Edinburgh.
Semester: AY.
Syllabus:
- Search algorithms (depth first search, breadth first search, uniform cost search, A* search)
- Constraint satisfaction problems;
- Games (min-max, alpha-beta pruning);
- Logic, resolution, introductory logic programming
- Knowledge representation – logic, rules, frames
- Goal and data-driven reasoning
- Practical rule-based programming
- Overview of main fields of AI (Vision, Learning, Knowledge Engineering)
- In depth view of one field of AI (e.g. Planning, Natural language)
- Autonomous agents
- Applications of AI
- AI programming
Learning Outcomes: Subject Mastery
- Critical understanding of traditional AI problem solving and knowledge representation methods
- Use of knowledge representation techniques (such as predicate logic and frames).
- Critical understanding of different systematic and heuristic search techniques
- Practice in expressing problems in terms of state-space search
- Broad knowledge and understanding of the subfields and applications of AI, such as computer vision, machine learning and expert systems.
- Detailed knowledge of one subfield of AI (e.g. natural language processing, planning) and ability to apply its formalisms and representations to small problems
- Detailed understanding of different approaches to autonomous agent and robot architectures, and the ability to critically evaluate their advantages and disadvantages in different contexts.
- Practice in the implementation of simple AI systems using a suitable language
- Can relate learned knowledge to work based computing scenario
Learning Outcomes: Personal Abilities
- Identification, representation and solution of problems
- Time management and resource organisation
- Research skills and report writing
- Practice in the use of ICT, numeracy and presentation skills
- Ability to communicate effectively with work colleagues on learned issues
Assessment Methods:
Assessment: Coursework 100%
Re-assessment: Coursework 100%
SCQF Level: 9.
Credits: 15.