Genetic algorithm optimizes parameters of multi-agent flocking models to match user-defined objectives, with alignment emerging from spacing maintenance.
Eventually, all you need is a simple evolutionary algorithm (for neuroevolution of continuous control policies) , isbn =
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NE 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
EvoFlock: evolved inverse design of multi-agent motion
Genetic algorithm optimizes parameters of multi-agent flocking models to match user-defined objectives, with alignment emerging from spacing maintenance.