Self-organizing robot fleets that outperform centralized systems through collective intelligence.
Robots trained in simulation environments to implicitly cooperate without explicit algorithmic instructions. Learning occurs collectively but execution happens individually without communication.
Probabilistic models infer the behavior of nearby agents without communication channels. Lookahead algorithms resolve potential conflicts through localized inference mechanisms.
Uniform decision policies applied to local perceptions generate emergent system-wide behaviors. Global efficiency patterns arise without explicit programming, increasing throughput beyond centralized coordination systems.
38%* reduction in travel distance
75%* increase in mean time between failures
52%* reduction in direction changes
74%* increase in system throughput
* evaluated against heuristic-based centralised search methods