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This course introduces major concepts and algorithms in Artificial Intelligence. Topics include problem solving, reasoning, games, and machine learning.
Covid-19 Update: Please refer to the course page on AKO | Learn for all information about your course, including lectures, labs, tutorials and assessments.In this course, you will explore a diverse array of techniques and methodologies aimed at developing computer programs that demonstrate intelligent behavior akin to that observed in humans and other animals. The curriculum covers a broad spectrum of topics that encapsulate the multifaceted nature of Artificial Intelligence (AI):- Planning- State-space search- Uninformed and informed graph search algorithms- Propositional logic and forward and backward chaining algorithms- Knowledge representation- Predicate logic and declarative programming- Constraint satisfaction problems, backtracking, and consistency-based algorithms- Optimisation, local and global search, heuristic and population-based algorithms- Belief networks and probabilistic inference algorithms- Machine learning (classification, regression, neural networks, learning parameters)- Games and adversarial search (minimax, alpha-beta pruning, more advanced methods)- Impacts of AI (ethical, societal, economical, etc.)
1. Identify problems amenable to transformation into state-space graphs or adversarial search, and employ known algorithms to solve them [WA1, WA2, WA3]2. Analyse and implement inference algorithms in both deterministic and non-deterministic contexts [WA1, WA2, WA3]3. Identify and resolve constraint satisfaction and optimisation problems using various techniques [WA1, WA2, WA3, WA5]4. Analyse and apply basic supervised machine learning algorithms for building predictive models [WA1, WA2, WA3, WA5]5. Analyse the complexities, limitations, and implications of using various AI algorithms and techniques WA2, WA4]
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
COSC262
Students must attend one activity from each section.
Depending on final student numbers, some of the advertised lab/tutorial streams may not run. Final lab/tutorial options will be available for self-allocation closer to the start of the semester through My Timetable.
Kourosh Neshatian
Covid-19 Update: Please refer to the course page on AKO | Learn for all information about your course, including lectures, labs, tutorials and assessments.
Poole, David L. and Mackworth, Alan K; Artificial Intelligence: Foundations of Computational Agents ; 3; Cambridge University Press, 2023.
Course Information on Learn
There are several important documents available online about departmental regulations, policies and guidelines at the following site. We expect all students to be familiar with these. Notices about this class will be posted to the class forum in the Learn system.COSC students will also be made members of a class called “CSSE Notices”, where general notices will be posted that apply to all classes (such as information about building access or job opportunities).
The Computer Science department's grading policy states that in order to pass a course you must meet two requirements:1. You must achieve an average grade of at least 50% over all assessment items.2. You must achieve an average mark of at least 45% on invigilated assessment items.If you satisfy both these criteria, your grade will be determined by the following University-wide scale for converting marks to grades: an average mark of 50% is sufficient for a C- grade, an average mark of 55% earns a C grade, 60% earns a C+ grade and so forth. However if you do not satisfy both the passing criteria you will be given either a D or E grade depending on marks. Marks are sometimes scaled to achieve consistency between courses from year to year.Students may apply for special consideration if their performance in an assessment is affected by extenuating circumstances beyond their control.Applications for special consideration should be submitted via the Examinations Office website within five days of the assessment. Where an extension may be granted for an assessment, this will be decided by direct application to the Department and an application to the Examinations Office may not be required. Special consideration is not available for items worth less than 10% of the course.Students prevented by extenuating circumstances from completing the course after the final date for withdrawing, may apply for special consideration for late discontinuation of the course. Applications must be submitted to the Examinations Office within five days of the end of the main examination period for the semester.
Please click HERE for the CSSE Department's policy for the academic remedy of applications for a special consideration for final exams.
Domestic fee $942.00
International fee $4,988.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
This course will not be offered if fewer than 10 people apply to enrol.
For further information see Computer Science and Software Engineering .