Spring 2022 Lectures, Playlists, and Files

Additional Resources for Spring 2022:

• Dropbox Folder of Resources for Spring 2022 Section of IEE/CSE 598
• YouTube Playlist of Lectures for Spring 2022 Section of IEE/CSE 598

Lecture Blog Posts in Chronological Order:

• Lecture 1A (2022-01-11): Introduction to Course, Metaheuristics, and Evolutionary Algorithms
  
• Lecture 1B (2022-01-13): The Evolutionary Approach to Engineering Design Optimization
• Lecture 1C (2022-01-18): Population Genetics of Evolutionary Algorithms
  
• Lecture 1D (2022-01-20): The Genetic Algorithm and its Implementation, Part 1
  
• Lecture 1E (2022-01-25): The Genetic Algorithm and its Implementation, Part 2
  
• Lecture 2A (2022-01-27): GA Approaches Beyond Optimization - Artificial Immune Systems
  
• Lecture 2B (2022-02-01): GA Approaches Beyond Optimization - AIS and Intro. to Evolutionary Programming
  
• Lecture 3A (2022-02-03): Introduction to Multi-criteria Decision Making and Pareto Optimality
  
• Lecture 3B (2022-02-08): Multi-Objective Genetic Algorithms (MOGA and Friends), Part 1
  
• Lecture 3C (2022-02-10): Multi-Objective Genetic Algorithms (MOGA and Friends), Part 2
  
• Lecture 4A (2022-02-15): From Multiobjective Genetic Algorithms to DGA, PGA, and Multimodal Optimization
  
• Lecture 4B  (2022-02-17): Niching Methods for Multi-modal Optimization
  
• Lecture 5A (2022-02-22): Introduction to Simulated Annealing and Maximum Entropy (MaxEnt) Methods
  
• Lecture 5B (2022-02-24): From MaxEnt Methods to MCMC Sampling
  
• Lecture 5C (2022-03-01): From MCMC Sampling to Optimization by Simulated Annealing
  
• Lecture 5D/6A (2022-03-03): Simulated Annealing Wrap-up and Distributed AI and Swarm Intelligence, Part 1 - Ant Colony Optimization (ACO)
  
• Lecture 6B (2022-03-15): Distributed AI and Swarm Intelligence, Part 2 - ACO and Introduction to Bacterial Foraging Optimization (BFO)
  
• Lecture 6C (2022-03-17): Distributed AI and Swarm Intelligence, Part 3 - BFO and Intro to Classical Particle Swarm Optimization (PSO) & Its Motivations
  
• Lecture 6D (2022-03-22): Distributed AI and Swarm Intelligence, Part 4 - Particle Swarm Optimization (PSO)
  
• Lecture 7A (2022-03-24): Introduction to Neural Networks
  
• Lecture 7B (2022-03-29): Introduction to Neural Networks: SLP, RBFNN, and MLP
  
• Lecture 7C (2022-03-31): Deep Neural Networks (UAT, MLP, and Backpropagation)
  
• Lecture 7D (2022-04-05): CNNs, Insect Brains, More Complex Neural Networks (TDNNs and RNNs)
  
• Lecture 7E (2022-04-07): RNNs and Their Training, LSTM, and Reservoir Machines
  
• Lecture 7F (2022-04-12): ANN Reinforcement Learning, Unsupervised Learning, Multidimensional Scaling, & Hebbian/Associative Learning
  
• Lecture 7G (2022-04-14): Decentralized Associative/Hebbian Learning and Intro. to Spiking Neural Networks and Neuromorphic Computing
  
• Lecture 7H (2022-04-19): From Spiking Neural Networks to Continual Learning and Beyond
  
• Lecture 8A (2022-04-21) – Split into two parts:
• Lecture 8A-Intro: Clarifications about Final Exam and Final Project
• Lecture 8A: Complex Systems Approaches to Computation - Interacting Particle Systems and the Voter Model
  
• Lecture 8B (2022-04-26): Elementary Cellular Automata, Computation, and Experimentation
  
• Lecture 8C (2022-04-28): Elementary Cellular Automata, Stochastic Cellular Automata, and Cellular Evolutionary Algorithms