Semester Two 2012
This course introduces Computational Intelligence computing concepts and demonstrates how they are used to solve problems that are normally difficult or intractable by conventional means. Topics covered include artificial intelligence programming languages, logic representations, biologically inspired algorithms and computer vision. Practical work will focus on solving sample problems using these various techniques.
This course introduces Artificial Intelligence (AI) techniques and demonstrates how they are used to solve problems that are normally difficult or intractable by conventional means.
The course covers core concepts in AI including problem solving by search, knowledge representation and reasoning, symbolic AI languages, decision making, biologically-inspired algorithms, learning and computer vision. Practical work will focus on solving sample problems using these various techniques.
In this course students will learn about artificial intelligence techniques and their applicability to real problems. They will design and implement artificial intelligence-based solutions to non-trivial
problems. Having completed the course students will be able to do the following:
* Know the conceptual model behind AI languages (Lisp and Prolog) and apply this knowledge to create efficient programs.
* Design and implement an expert system that operates in a realistic problem domain
* Represent concepts and logic computationally in several different ways and compare and contrast the capabilities and limitations these representations
* Design solutions for problems involving uncertain inputs or outcomes
* Apply heuristic search to optimisation problems
* Describe techniques for computer vision and compare their strengths and weaknesses
* Describe how artificial intelligence is used in advanced education software and what benefits this brings to the student (or teacher)
* Apply machine learning algorithms to real data sets to build predictive models
* Knowledge of current and emerging AI technologies
* The ability to design and implement computing solutions using artificial intelligence techniques
* The ability to objectively compare AI techniques and use the right ones to develop an appropriate solution
Course Coordinator / Lecturer
17 Aug 2012
12 Oct 2012
Examination and Formal Tests
02 Nov 2012
Stuart Russell, Peter Norvig;
Artificial Intelligence: A Modern Approach;
Prentice Hall, 2009.
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Additional Course Outline Information
Course Outline is available here: http://www.cosc.canterbury.ac.nz/open/teaching/classes/cosc367/outline.pdf
This course will not be offered if fewer than 10 people apply to enrol.
For further information see
Computer Science and Software Engineering.
All COSC367 Occurrences
Semester Two 2012