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Artificial intelligence is the quest to create intelligent agents that can complete complex tasks which are at present only achievable by humans. This broad field covers logic, probability, perception, reasoning, learning and action; and everything from Mars Rover robotic explorers to the Watson Jeopardy playing program. You will explore some of the vast area of artificial intelligence. Topics covered include: searching, problem solving, reasoning, knowledge representation and machine learning. Topics may also include some of the following: game playing, expert systems, pattern recognition, machine vision, natural language, robotics and agent-based systems.
- Agents and search
- Probabilistic reasoning
- Reinforcement Learning
- Pattern recognition for robotics.
Intended learning outcomes
On completion of this subject the student is expected to:
- Identify problems that can be solved by search, and create search-based solution algorithms
- Design intelligent agents
- Choose the best search-based solving methods for a particular problem
- Make use of formal approaches for representing and reasoning about knowledge
- Build systems that use simple learning approaches to improve their performance
On completion of this subject students should have developed the following generic skills:
- The ability to analyse and solve problems involving complex reasoning
- The ability to synthesise information and communicate results effectively
- The capacity for critical and independent thought and reflection
- The ability to apply knowledge of basic science and engineering fundamentals
- The ability to undertake problem identification, formulation and solution.
Last updated: 20 February 2024