Advancing Swarm Intelligence
Arboria Labs studies how local rules and decentralized coordination produce robust collective behavior at extreme scale — and, specifically, what happens to that coordination when agents cannot see each other in real time. We build the simulation stack, run the experiments, and publish what we measure.
Start here
New to the field? Read what swarm intelligence is, then the key principles that make it work. Here for the results? The research index is the shortest path, and The Delay Cliff is where the through-line starts. Curious about the software? The toolchain documentation describes all three engines. Looking to collaborate? See Team and Contact.
Unifying Swarm Intelligence and Distributed Systems
Swarm intelligence and distributed systems are two halves of one problem: coordinate many agents under local information, bounded communication, and partial failure. We work across both — adaptive flocking and stigmergic coverage on one side, CRDT-based intent and delay-tolerant networking on the other — with measurement-first instrumentation that maps local parameter choices to global regime behavior.
Integrated Arboria Framework
Three proprietary engines, each doing one job. The Leviathan Engine is a C++ simulation core that advances agent states under physics, a range-limited communication model with real bandwidth and energy costs, and fault injection. Gossamer Threaded Intelligence supplies the coordination primitives, tasks, predictors, and metrics that decide what each agent does and score how well the collective did it. Maneuver.Map orchestrates experiments across a cloud job array, captures provenance, and renders the result in the browser.
Our Focus Areas
Coordination under communication delay
Every decentralized coordination result you have read assumes agents see their neighbours now. Take that away and coordination quality collapses — through a boundary near 10–20 steps of delay, identically across gossip, flocking, and CRDT-intent propagation, and identically at 500 or 2,000 agents. Cheap peer-state prediction pushes the boundary outward. This is the lab’s central result and the science that everything else rests on.
Orbital compute constellations
Communication delay in orbit is light-lag, and it is not negotiable. As datacenter hardware moves to orbit for uninterrupted solar power and radiative cooling, the constellations that host it must schedule work, route intent, and hold formation across links that come and go on orbital timescales. We build the digital twin and the decentralized, energy-aware scheduler that make that tractable.
Our Research Ethics
Autonomous collectives have a specific set of risks that are not addressed by generic AI ethics. We take them seriously:
Dual-use caution. Swarm methods can be used for surveillance, denial, and coercion. We do not contribute directly to lethal autonomous weapons and we gate publications that could materially accelerate them.
Orbital and planetary responsibility. Large deployments in space create Kessler-syndrome risk and planetary contamination risk. Our simulations and recommendations treat debris, deorbit, and forward-contamination as first-order constraints.
Reproducibility over spectacle. Every published result names the batch it came from and records the environment that produced it. Our engines are proprietary, which limits what external reproduction can mean; we say so plainly rather than promising more than we can deliver. See Reproducibility and Data Availability.
Careful claims. Our results come from a simplified kinematic simulator. They are claims about coordination algorithms, not validation of physical devices, and we scope them to the fidelity that backs them — anchoring against known external results wherever we can.
Learn more about our principles →
Latest Updates
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Arboria Labs: swarm intelligence and distributed systems research, measurement-first.