Additional Resources for Spring 2025:
Lecture Blog Posts in Chronological Order:
- 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): From DGA/PGA to Niching Methods for Multi-modal Optimization
- Lecture 4C (2025-03-04): Niching Methods in Multi-Modal Optimization
- Lecture 5A (2025-03-18): Introduction to Simulated Annealing and Entropy
- Lecture 5B (2025-03-20): From Maximum Entropy (MaxEnt) Methods Toward Optimization by Simulated Annealing
- Lecture 5C (2025-03-25): Toward: Introduction to Boltzmann sampling and Monte Carlo integration
- Lecture 5D/6A (2025-03-27): Simulated Annealing Wrap-up and Distributed AI and Swarm Intelligence, Part 1 - Introduction to Ant Colony Optimization (ACO)
- Lecture 6B (2025-04-01): Distributed AI and Swarm Intelligence, Part 2 – ACO and Introduction to Bacterial Foraging Optimization (BFO)
- Lecture 6C (2025-04-03): Distributed AI and Swarm Intelligence, Part 3 – Bacterial Foraging Optimization (BF) and Particle Swarm Optimization (PSO)
- Lecture 7A (2025-04-08): Neural Foundations of Learning
- Lecture 7B (2025-04-10): Feeding Forward from Neurons to Networks (SLP, RBFNN, MLP, CNN)
- Lecture 7C (2025-04-15): Recurrent Networks and Temporal Supervision
- Lecture 7D (2025-04-17): Reinforcement Learning – Active Learning in Rewarding Environments
- Lecture 7E (2025-04-22): Learning without a Teacher – Unsupervised and Self-Supervised Learning
- Lecture 7F (2025-04-24): Spiking Neural Networks and Neuromorphic Computing
- Lecture 8A (2025-04-29): Complex Systems Models of Computation – Cellular Automata and Neighbors
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