An-Najah Staff

week

Topics

1

Introduction to AI, turing test, domains of AI, search space, problem examples

2

Searching for problem solution(s), search tree, data structure for search tree, Search strategies and their evaluation, uninformed vs. informed strategies, breadth first search strategy and implementation, evaluation of breadth first strategy

3

depth first search strategy, implementation and evaluation, avoiding repeated states, Uniform cost search and its evaluation, heuristics

4

best first search , A* search, admissability, Hill climbing search

5

introduction to game playing algorithms, mini-max algorithm

6

Approximations, Alpha-beta pruning algorithm, tracing examples, first exam

7

Introduction to knowledge representation, characteristics of a good knowledge representation, propositional logic

8

Predicate logic, clause form

9

Converting from predicate logic to clause from, unification

10

Resolution algorithm, examples

11

Knowledge representation and inference in Prolog, variables, clauses, program execution, input/output, fail predicate

12

Recursion in prolog, cut predicate, dynamic facts, Second exam

13

Knowledge representation under uncertainty: Discrete random variables, unconditional and conditional probability, Bays rule, representing worlds using joint probability distributions Bayesian networks, semantics of Bayesian networks, computing joint probabilities from Bayesian network, application examples

14

Learning decision trees

15

Neural networks