Explores Ant Colony Optimization (ACO) for routing and optimization, discussing constructive heuristics, local search, pheromone mechanisms, and real-world applications.
Explores the trade-off between complexity and risk in machine learning models, the benefits of overparametrization, and the implicit bias of optimization algorithms.
Covers the general logistics, course rationale, prerequisites, organization, credits, workload, grading, and course content, including swarm intelligence, foraging strategies, and collective phenomena.
Explores combinatorial optimization using simulated annealing to find ground states in frustrated systems and address challenges in satisfying all interactions simultaneously.
