This course is required for the Smart Systems Stream, and is an elective for the Visual Computing and Games Stream.

Prerequisites:  COMP 2001 or the former COMP 2710,  COMP 2002 or the former COMP 2711, and Statistics 2500 or Statistics 2550

Availability: This course is usually offered once per year, in Fall or Winter.

Course Objectives

This course covers basic algorithmic techniques and data structures that are used to embed basic intelligent behaviors, such as problem solving, reasoning and learning in software systems and agents.

Representative Workload

• Assignments (5) 45%
• Tests (2) 30%
• Final Exam 25%

Representative Course Outline

• Background: AI and Agents (3 hours)
• AI definition and areas
• Agent definition, structure and types
• Search (10 hours)
• Exhaustive search
• Heuristic search
• Local search (such as hill-climbing)
• Constraint satisfaction
• Adversarial search
• Search under uncertainty
• Logical Reasoning (9 hours)
• Knowledge-based systems
• Reasoning
• Planning
• Fuzzy logic
• Probabilistic Reasoning (8 hours)
• Quantifying uncertainty
• Bayesian networks
• Dynamic Bayesian Networks

Notes

• Credit cannot be obtained for both Computer Science 3200 and the former Computer Science 4753.

Page last updated May 24th 2021