Fundamentals of swarm intelligence (stability analysis, swarm aggregation, swarm in known and unknown environments, dynamic optimization);
Swarm-based metaheuristics (theoretical foundations, swarm clustering and sorting, Particle Swarms, Ant Colony, Artificial Bees, Fireflies Algorithm, Bacterial Foraging, recent advances and and new inspirations);
Applications (swarm robotics, internet computing, software engineering, sensors, data mining) regarding different optimization problems, finding optimal routes, scheduling, routing, structural optimization, image and data analysis.
Previous knowledge
The course prerequisites include programming skills and fundamental knowledge of agent-based modeling, probability calculus and analysis (differential equations, continuous and discrete time).