Additional Resources for Spring 2025:
Lecture Blog Posts in Chronological Order:
(unlinked lecture titles are what is tentatively planned for the future)
- Lecture 1A (2025-01-14): Introduction to the Course, Its Policies, and Its Motivations
- Lecture 1B (2025-01-16): The Evolutionary Approach to Engineering Design Optimization
- Lecture 1C (2025-01-21): Population Genetics of Evolutionary Algorithms
- Lecture 1D (2025-01-28): The Four Forces of Evolution and the Drift Barrier
- Lecture 1E (2025-01-30): The Basic Genetic Algorithm and its Implementation
- Lecture 1F (2025-02-04): GA Wrap Up – Options for Selection, Crossover, Mutation, and Extensions
- Lecture 2A (2025-02-06): Evolutionary Computing from Optimization to Programming (Mutation, CMA-ES, and Evolutionary Programming)
- Lecture 2B (2025-02-11): Genetic Programming, Immunocomputing, and Artificial Immune Systems
- Lecture 2C (2025-02-13): Immunocomputing: Genetic Approaches for Diverse Solution Portfolio
- Lecture 3A (2025-02-18): Multi-Criteria Decision Making, Pareto Optimality, and an Introduction to Multi-Objective Evolutionary Algorithms (MOEA's)
- Lecture 3B (2025-02-20): Multi-Objective Genetic Algorithms: Weight/Vector-Based Approaches
- Lecture 3C/4A (2025-02-25): Pareto Ranking and Moving from Communities to Meta-Populations (DGA, PGA)
- Lecture 4B (2025-02-27): Niching Methods for Multi-modal Optimization
- Lecture 5A (2025-03-04): Introduction to Simulated Annealing and Maximum Entropy (MaxEnt) Methods
- Lecture 5B (2025-03-18): From MaxEnt Methods to MCMC Sampling
- Lecture 5C (2025-03-20): From MCMC Sampling to Optimization by Simulated Annealing
- Lecture 5D/6A (2025-03-25): Simulated Annealing Wrap-up and Distributed AI and Swarm Intelligence, Part 1 - Ant Colony Optimization (ACO)
- Lecture 6B (2025-03-27): Distributed AI and Swarm Intelligence, Part 2 - ACO and Introduction to Bacterial Foraging Optimization (BFO)
- Lecture 6C (2025-04-01): Distributed AI and Swarm Intelligence, Part 3 - BFO and Intro to Classical Particle Swarm Optimization (PSO) & Its Motivations
- Lecture 6D (2025-04-03): Distributed AI and Swarm Intelligence, Part 4 - Particle Swarm Optimization (PSO)
- Lecture 7A (2025-04-08): Introduction to Neural Networks
- Lecture 7B (2025-04-10): Introduction to Neural Networks: SLP, RBFNN, and MLP
- Lecture 7C (2025-04-15): Deep Neural Networks (UAT, MLP, and Backpropagation)
- Lecture 7D (2025-04-17): CNNs, Insect Brains, More Complex Neural Networks (TDNNs and RNNs)
- Lecture 7E (2025-04-22): RNNs and Their Training, LSTM, and Reservoir Machines
- Lecture 7F (2025-04-24): ANN Reinforcement Learning, Unsupervised Learning, Multidimensional Scaling, & Hebbian/Associative Learning
- Lecture 7G (2025-04-29): Decentralized Associative/Hebbian Learning and Intro. to Spiking Neural Networks and Neuromorphic Computing
- Lecture 8A (2025-05-01): Complex Systems Approaches to Computation - Interacting Particle Systems and the Voter Model
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