Additional Resources for Spring 2022:
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
No comments:
Post a Comment