Nineteen declared organization patterns with deterministic step algorithms and varying maturity.
47 · Collective Intelligence
Dynamic organizations
in GenOS.
Nineteen declared organization patterns with deterministic step algorithms and varying maturity.
DEFINITION AND SCIENCE
What it means
in GenOS.
Organization science and distributed algorithms study how coordination rules shape decisions. These nineteen software patterns declare roles and transitions; their existence does not demonstrate group effectiveness.
Biological groups can organize through local roles and interactions. The GenOS patterns are authored coordination rules; observed group success requires separate tests.
Nineteen declared organization patterns with deterministic step algorithms and varying maturity.
Model organization O=(members, roles, edges, decision rule). At each step, transition T_O(state,input) must preserve authority and resource invariants.
ANIMATED DIAGRAM · INTERACTIVE MODEL
01 / 03Explore the mechanism: Dynamic organizations
A qualitative teaching model of this concept. It does not run GenOS or validate its implementation.
01Choose organization ruleINPUT
02Assign members and edgesMECHANISM
03Apply decision procedureCONDITIONAL OUTCOME
Current transition · Step 1Choose organization rule
The modeled transition may proceed. Change the assumption and move through the stages to inspect the decision path.
PROCESS AND USE
How it works
at a glance.
Choose organization rule
Nineteen declared organization patterns with deterministic step algorithms and varying maturity.
Assign members and edges
Model organization O=(members, roles, edges, decision rule). At each step, transition T_O(state,input) must preserve authority and resource invariants.
Apply decision procedure
Apply decision procedure. Organization science and distributed algorithms study how coordination rules shape decisions. These nineteen software patterns declare roles and transitions; their existence does not demonstrate group effectiveness.
RUNTIME IMPLEMENTATION
What is connected,
and how far.
The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.
The organization registry and deterministic runStep policies are executable and tested; registry presence does not establish selection, dispatch or improved mission outcomes.
Failure modes have not yet been separately cataloged for this entry; follow the source and evidence links before relying on the mechanism.
PRIMARY RESEARCH · MECHANISM LEVEL
The mechanism
behind the analogy.
Flocks, herds, and schools: A distributed behavioral model
Craig W. Reynolds · Computer Graphics 21(4), 25–34
Presents a computational flocking model. It supports discussion of local coordination rules, not a general claim that a multi-agent system is intelligent or robust.
Open publication ↗The Byzantine Generals Problem
Leslie Lamport, Robert Shostak, and Marshall Pease · ACM Transactions on Programming Languages and Systems 4(3), 382–401
Formalizes agreement under specified faulty-participant assumptions. A voting topology does not inherit Byzantine fault tolerance unless its protocol meets those assumptions.
Open publication ↗Primary research describes the cited mechanism; specific technologies may instead cite their original technical documentation. These sources provide context and do not validate the GenOS implementation.
EVIDENCE AND LIMITS
Scope and validation boundaries
The linked, versioned GenOS source defines this concept's supported operations and limits. The status axes describe the implementation and evidence recorded for this entry; they do not establish general mission success, scientific equivalence or behavior beyond that scope.