Swarm Intelligence Algorithms - Session Interview With Frances Buontempo
summary
Demonstrates a working swarm optimizer that finds optimal XY positions by simulating tens to hundreds of independent agents with position and velocity, each nudged toward its personal best and the global best using simple add/subtract/multiply updates. Implements particle swarm and a playful cat swarm algorithm in C++ and SFML, uses reproducible pseudo random numbers, shows live graphics, and explains testing strategies for stochastic code so the simulation actually converges on solutions.
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