Lectures

Edit 0 27 …
No.
 Date
 Topics
 Lecture
 References
1
 25/08
 Introduction, Course Overview
CI Unit 1- Intro.pdf
2
 01/09
 Intro of Evolutionary Algorithms, Swarm Intelligence, Neural Networks, Reinforcement Learning, Fuzzy Logic

3
 03/09
 Evolutionary Computation - Evolutionary Process, genes, chromosomes, Survival of the fittest, Exploration vs Exploitation
CI Unit 2 - EA.pdf
4
 08/09
 Problem formulation in EA,
Crossover, Mutation
Using EA to solve Traveling Salesman problem

5
 10/09
 Parent Selection & Survivor Selection mechanisms
CI Unit 3 - EA.pdf
6
 15/09
 Discussion on Assignment 1,
EA Performance Indicators, NFL Theorem
CI Unit 4 - EA Evaluation.pdf

 Assignment #1 (Part 1) - due on 22nd Sep
7
 17/09
 Evolutionary Programming and Evolutionary Strategies, Uniform & Gaussian mutations
CI Unit 5 - ES, EP.pdf
8
 22/09
 Genetic Algorithms,
Discussion on Assignment 1 (Part 1)
CI Unit 6 - Genetic Algorithm.pdf
9
 24/09
 Artificial Neural Networks
CI Unit 7 - ANN.pdf

 Reading Assignment 1
-
EvolvingCheckers.pdf


Term Exam - I and Eid Holidays

10
 13/10
 Artificial Neural Networks - Backpropagation

11
 15/10
 Building Pacman Controller
CI Unit 8 - Programming with Pacman.pdf

 Assignment # 2 - Building ANN based pacman controller
Assignment 2.pdf
12
 20/10
 Swarn Intelligence: Ant Colony Optimization (ACO)
CI Unit 9 - ACO.pdf
13
 22/10
 ACO, Review of Term Exam I copies

14
 27/10
 Particle Swarm Optimization (PSO)
CI Unit 10 - PSO.pdf
15
 29/10
 Review of Assignment 2 - Building pacman controller using PSO optimized neural network

16
 05/11
 Simulated Annealing, Tabu Search
CI Unit 11 - Simulated Annealing, Tabu Search.pdf
17
 10/11
 Artificial Immune System
Differential Evolution
CI Unit 12 - AIS.pdf
CI Unit 13 - Differential Evolution.pdf

 Assignment 3 (Due on 24th Nov) : Optimize the functions given in Assignment 1 using AIS
18
 12/11
 Review of Assignment 2 - Evolutionary Neural Network based pacman controller

19
 24/11
 Reinforcement Learning, Markov Decision Process (MDP), Reward, Policy, RL vs EA
CI Unit 14 - Reinforcement Learning.pdf
20
 26/11
 Reinforcement Learning: Reward vs Values, Value Iteration Algorithm
Project: Evolving tic-tac-toe agent using Reinforcement Learning
Due at the end of semester
21
 01/12
 Episodic learning, Temporal Difference Learning, Action Selection Policies (e-Greedy, Softmax)

22
 03/12
 QLearning, Function Approximation
CI Unit 15 - QLearning.pdf
23,24
 08/12
 Class Presentations
 Presentation Slides
25
 15/12
 Class Presentation, Review of Mid term 2 Copies, Project Discussion

26,27
 17/12
 Fuzzy Logic and Reasoning
CI Unit 16 - Fuzzy Logic.pdf
28,29
 21/12
 Project Presentations