COMP9414 Artificial Intelligence 2018S1
ALL CODES SHOULD BE APPROPRIATELY REFERENCED, COPYING MAY RESULT IN PLAGIARISM
Lecturer: Alan Blair
Main Contents
- Environment and Agent : PEAS Description, Agent Types, Enviornment Classification.
- Prolog Programming : Queries, Recursion, Loop, Manipulation of Lists (Head and Tail), Sorting, Structures...
- Path Searching : Uninformed Search (BFS, DFS, IDS...), Heuristic Search (UCS, A-Star, Greedy), Time and Space Complexity.
- Path Searching Application : Graph Search, Maze Search, 8-puzzle Problem, Heuristic Path Algorithm.
- Game Playing : Tic-Tac-Toe, Alpha-Beta Search and Alpha-Beta Pruning.
- Decision Tree and Learning : Decision Trees, Information Entropy and Minimal Entropy Principle, Laplace Pruning.
- Perceptron : Classifiers, Iterative Training.
- Neural Networks : Single Neuron, Multi-layer Neural Networks Design, Gradient Descent, Forward Pass and Backpropagation.
- Constraint Satisfication : Map-Coloring, 8-queens Problem, Backtracking, Forward Checking, Arc-Consistency, Local Search (Hill Climbing, Simulated Annealing).
- Logic : Validity and Satisfiability, Propositional Logic Solution, First-Order Logic Sentences.
- Uncertainty : Conditional Probability, Enumerating Probabilities.
Assessment Details
- Assignment 1 : Logical Queries, Manipulation of Lists and Trees. Mark:12/12.
- Assignment 2 : Prolog Tests of Path Search Methods (Efficiency and optimum), Heuristic Algorithm, Maze Search, Distance Calculation . Mark:10/10.
- Assignment 3 : Prolog Project with using complex list manipulation and logic. Mark:17.2/18.
Disclaimer
- No responsibility will be taken if some mistakes influence your mark. It is better to check before referencing.
- No responsibility will be taken if copying codes results in detected plagiarism.