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COMP2208: Intelligent Systems

Second Year, 2024/25 · Semester 1

Overall mark 89%

AI problem-solving through search, planning, constraint satisfaction, and probabilistic reasoning.

SKILLS Search Algorithms · Problem Formulation · Constraint Satisfaction · Probabilistic Reasoning

TECHNOLOGIES Theory

What the module covered

This module introduced several approaches to artificial intelligence. We studied uninformed and heuristic search, including A*, local search, and genetic algorithms, then applied search ideas to constraint satisfaction, game playing with minimax and alpha-beta pruning, and planning.

It also introduced decision trees, nearest-neighbour classification, and Bayesian networks, alongside questions about what it means for a system to behave intelligently.

What I took from it

A central idea was that the way a problem is represented shapes how it can be solved. Defining the states, available actions, goal, and costs makes it possible to compare search strategies and understand the tradeoffs between speed, memory use, and solution quality.