Our Lab
Arboria Labs is a research organization studying swarm intelligence and distributed systems for autonomous robotics and orbital operations. We design coordination algorithms, build the simulation stack that tests them, and publish what we measure — including the results that did not go our way.
The lab’s work is organized around a single question. Nearly every decentralized coordination result in the literature assumes an agent can see its neighbours now. Take that assumption away — introduce real delay, finite bandwidth, energy per bit, packet loss — and coordination behaves very differently, and in ways the standard models do not anticipate. Mapping where and how it breaks is the thread running through everything on the research index.
How we work
Measurement first. Every published figure names the experiment batch it came from and records the environment that produced it. When a number moves, we want to know which change moved it — so the coordination layer is pinned by cryptographic fingerprints that fail loudly the moment a refactor perturbs a published result.
Scoped to the fidelity that backs it. Our results come from a simplified kinematic simulator. They are claims about coordination algorithms, not validation of physical hardware, and we say so in each paper rather than letting the framing imply more than the evidence supports.
Negative results are results. Two of our own hypotheses have been refuted by our own instrumentation, and both refutations are published in the papers that originally advanced them. A lab that only reports its wins is not measuring; it is advertising.
These commitments are set out in full on the Arboria Principles page.
The toolchain
Three engines, each doing one job. Leviathan Engine is a C++ 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 information-theoretic metrics. Maneuver.Map orchestrates experiments across a cloud job array, captures provenance, and renders the results in the browser. The toolchain overview describes all three.
People
Chris Adams — Founder, Research Lead
Chris leads Arboria Labs’ research program and builds the core toolchain. His background spans distributed systems engineering, simulation infrastructure, and applied machine learning.
ORCID · chris@arborialabs.com · chrisadams.io
Collaborate
We publish papers, build tooling, and welcome collaborations with academic groups and industry teams working on related problems. The Community page lists the peer labs and programs we follow. To discuss partnerships, shared datasets, or student internships, write to community@arborialabs.com.
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