SC3000 - Artificial Intelligence
Course Summary
Introduction Jan 19 (Fri) - 2 Intelligent Agents Jan 23 (Tue) - 3 Uninformed Search Jan 26 (Fri) - 4 Informed Search Jan 30 (Tue) - 5 Constraint Satisfaction 1 Feb 02 (Fri) - 6 Adversarial Search Feb 06 (Tue) - 7 Markov Decision Process 1 Feb 09 (Fri) - 8 Markov Decision Process 2 Feb 13 (Tue) - 9 Reinforcement Learning 1 Feb 16 (Fri) - 10 Reinforcement Learning 2 Feb 20 (Tue) - 11 Game Theory Feb 23 (Fri) - 12 Introduction to GPT
Workload
If you follow the online answers for the labs, this module basically only has a final exam. The search topics are covered in SC1015, so they’re not new. Prof Yu Han emails tutorial answers to his tutorial groups.
Projects
There are 2 take-home labs worth 40% of the grade, and a final exam worth 60%.
Tips to Do Well
Lab answers are available online, so make use of them. Also, note that using Prolog for a lab feels quite outdated.
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