{
  "name": "BraInference knowledge graph",
  "count": 109,
  "links": 138,
  "layers": [
    "Infrastructure",
    "Physics",
    "Mind",
    "Society"
  ],
  "patterns": [
    {
      "handle": "FractionalMetaModel",
      "ref": "FractionalMetaModel#3eca",
      "layer": "Infrastructure",
      "category": "Data Structures",
      "gloss": "A model at the level of the solution that partly implements several models at once",
      "url": "/knowledge-graph/FractionalMetaModel/",
      "json": "/knowledge-graph/FractionalMetaModel.json"
    },
    {
      "handle": "SecondOrderInteractionNetwork",
      "ref": "SecondOrderInteractionNetwork#8c66",
      "layer": "Infrastructure",
      "category": "Data Structures",
      "gloss": "Promote each timed interaction to a node and link interactions that follow each other through a shared participant",
      "url": "/knowledge-graph/SecondOrderInteractionNetwork/",
      "json": "/knowledge-graph/SecondOrderInteractionNetwork.json"
    },
    {
      "handle": "StressorIncidenceMatrix",
      "ref": "StressorIncidenceMatrix#3406",
      "layer": "Infrastructure",
      "category": "Data Structures",
      "gloss": "A stressors-by-components matrix showing which parts each possible stressor would force to change",
      "url": "/knowledge-graph/StressorIncidenceMatrix/",
      "json": "/knowledge-graph/StressorIncidenceMatrix.json"
    },
    {
      "handle": "ComputationalChannel",
      "ref": "ComputationalChannel#4dbe",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "A channel formed by a generator language and an acceptor language, where rejection is computation, not noise",
      "url": "/knowledge-graph/ComputationalChannel/",
      "json": "/knowledge-graph/ComputationalChannel.json"
    },
    {
      "handle": "ComputationalEntropyRate",
      "ref": "ComputationalEntropyRate#ae56",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "Bits submitted per bit accepted in a computational channel, a measure of work done rather than noise",
      "url": "/knowledge-graph/ComputationalEntropyRate/",
      "json": "/knowledge-graph/ComputationalEntropyRate.json"
    },
    {
      "handle": "ComputationalFlowRatio",
      "ref": "ComputationalFlowRatio#fb62",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "Bit flow rate over input flow rate: how cheaply a channel rejects, at a given entropy rate",
      "url": "/knowledge-graph/ComputationalFlowRatio/",
      "json": "/knowledge-graph/ComputationalFlowRatio.json"
    },
    {
      "handle": "DegreeEntropy",
      "ref": "DegreeEntropy#a793",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "Entropy of how connectivity is spread over the nodes of a network: local heterogeneity",
      "url": "/knowledge-graph/DegreeEntropy/",
      "json": "/knowledge-graph/DegreeEntropy.json"
    },
    {
      "handle": "JensenShannonDivergence",
      "ref": "JensenShannonDivergence#b3b4",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "A symmetric, bounded distance between two distributions, built from their mixture",
      "url": "/knowledge-graph/JensenShannonDivergence/",
      "json": "/knowledge-graph/JensenShannonDivergence.json"
    },
    {
      "handle": "ProductivePredictionMachine",
      "ref": "ProductivePredictionMachine#7783",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "Simplify an automaton by deleting the paths a reliable prediction says inputs will never take",
      "url": "/knowledge-graph/ProductivePredictionMachine/",
      "json": "/knowledge-graph/ProductivePredictionMachine.json"
    },
    {
      "handle": "ReversibleComposability",
      "ref": "ReversibleComposability#4aa2",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "Parts join through interfaces whose effects and side-effects are fully undoable",
      "url": "/knowledge-graph/ReversibleComposability/",
      "json": "/knowledge-graph/ReversibleComposability.json"
    },
    {
      "handle": "ShannonEntropy",
      "ref": "ShannonEntropy#a177",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "The average surprise of a distribution: how many bits it takes to predict an outcome",
      "url": "/knowledge-graph/ShannonEntropy/",
      "json": "/knowledge-graph/ShannonEntropy.json"
    },
    {
      "handle": "SpectralEntropy",
      "ref": "SpectralEntropy#d557",
      "layer": "Infrastructure",
      "category": "Primitives",
      "gloss": "Entropy of a graph Laplacian's eigenvalues: the diversity of global flow and relaxation modes",
      "url": "/knowledge-graph/SpectralEntropy/",
      "json": "/knowledge-graph/SpectralEntropy.json"
    },
    {
      "handle": "ClusteredObservationTesting",
      "ref": "ClusteredObservationTesting#5f8e",
      "layer": "Infrastructure",
      "category": "Verification",
      "gloss": "Many windows from few samples are not many samples: test at the level where independence holds",
      "url": "/knowledge-graph/ClusteredObservationTesting/",
      "json": "/knowledge-graph/ClusteredObservationTesting.json"
    },
    {
      "handle": "MotivatedInstrumentTuning",
      "ref": "MotivatedInstrumentTuning#ed8f",
      "layer": "Infrastructure",
      "category": "Verification",
      "gloss": "Investigators who need a result tune their instruments toward it, often without intent",
      "url": "/knowledge-graph/MotivatedInstrumentTuning/",
      "json": "/knowledge-graph/MotivatedInstrumentTuning.json"
    },
    {
      "handle": "NullModelBaseline",
      "ref": "NullModelBaseline#9d36",
      "layer": "Infrastructure",
      "category": "Verification",
      "gloss": "Attribute structure to a mechanism only by beating a baseline that keeps everything except that mechanism",
      "url": "/knowledge-graph/NullModelBaseline/",
      "json": "/knowledge-graph/NullModelBaseline.json"
    },
    {
      "handle": "AdaptiveNetworkCoevolution",
      "ref": "AdaptiveNetworkCoevolution#e588",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Agent states and the network linking them reshape each other on comparable timescales",
      "url": "/knowledge-graph/AdaptiveNetworkCoevolution/",
      "json": "/knowledge-graph/AdaptiveNetworkCoevolution.json"
    },
    {
      "handle": "AsynchronousDomainHedge",
      "ref": "AsynchronousDomainHedge#ebb2",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Concurrent niche hedging on shared code sites predicts overlapping coding sequences",
      "url": "/knowledge-graph/AsynchronousDomainHedge/",
      "json": "/knowledge-graph/AsynchronousDomainHedge.json"
    },
    {
      "handle": "EmergentRuleSearch",
      "ref": "EmergentRuleSearch#9c19",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Vary the rules of simple agents in simulation to see which yield interesting collective behavior",
      "url": "/knowledge-graph/EmergentRuleSearch/",
      "json": "/knowledge-graph/EmergentRuleSearch.json"
    },
    {
      "handle": "EntropyDensityCollapse",
      "ref": "EntropyDensityCollapse#0874",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Rescale entropy and density by system size until all samples fall on one curve, then read regimes from the residue",
      "url": "/knowledge-graph/EntropyDensityCollapse/",
      "json": "/knowledge-graph/EntropyDensityCollapse.json"
    },
    {
      "handle": "EquationReduction",
      "ref": "EquationReduction#c553",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Compress a complex phenomenon into a short interpretable equation",
      "url": "/knowledge-graph/EquationReduction/",
      "json": "/knowledge-graph/EquationReduction.json"
    },
    {
      "handle": "NicheHedgeCrossing",
      "ref": "NicheHedgeCrossing#65e3",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Cross a fitness valley by paying each step in a simpler niche where the broken intermediate helps",
      "url": "/knowledge-graph/NicheHedgeCrossing/",
      "json": "/knowledge-graph/NicheHedgeCrossing.json"
    },
    {
      "handle": "RedQueenRace",
      "ref": "RedQueenRace#4c87",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "In co-evolving niches, adapting keeps you in place rather than moving you ahead",
      "url": "/knowledge-graph/RedQueenRace/",
      "json": "/knowledge-graph/RedQueenRace.json"
    },
    {
      "handle": "SelfOrganisation",
      "ref": "SelfOrganisation#efc9",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Global order that arises from local interactions, with no component holding the blueprint",
      "url": "/knowledge-graph/SelfOrganisation/",
      "json": "/knowledge-graph/SelfOrganisation.json"
    },
    {
      "handle": "SpatioTemporalNullModel",
      "ref": "SpatioTemporalNullModel#3576",
      "layer": "Physics",
      "category": "Dynamics",
      "gloss": "Simulate agents that move like the real ones but ignore each other, to test for social structure",
      "url": "/knowledge-graph/SpatioTemporalNullModel/",
      "json": "/knowledge-graph/SpatioTemporalNullModel.json"
    },
    {
      "handle": "ComputationalIrreducibility",
      "ref": "ComputationalIrreducibility#77ea",
      "layer": "Physics",
      "category": "Primitives",
      "gloss": "Some processes have no shortcut: the only way to know step n is to run n steps",
      "url": "/knowledge-graph/ComputationalIrreducibility/",
      "json": "/knowledge-graph/ComputationalIrreducibility.json"
    },
    {
      "handle": "ActiveInferenceHomeostasis",
      "ref": "ActiveInferenceHomeostasis#1892",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Baked-in survival ranges become priors, and gaps between prior and state drive action",
      "url": "/knowledge-graph/ActiveInferenceHomeostasis/",
      "json": "/knowledge-graph/ActiveInferenceHomeostasis.json"
    },
    {
      "handle": "AdaptiveSplineSeparator",
      "ref": "AdaptiveSplineSeparator#6cd0",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Fit a curve through a 2-D scatter that maximally separates two groups, to catch oblique separation",
      "url": "/knowledge-graph/AdaptiveSplineSeparator/",
      "json": "/knowledge-graph/AdaptiveSplineSeparator.json"
    },
    {
      "handle": "ArchitectureOfIntelligence",
      "ref": "ArchitectureOfIntelligence#edd7",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Intelligence as composable structure with local learning, durable state, and prediction",
      "url": "/knowledge-graph/ArchitectureOfIntelligence/",
      "json": "/knowledge-graph/ArchitectureOfIntelligence.json"
    },
    {
      "handle": "BorrowedMortality",
      "ref": "BorrowedMortality#d412",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "A learner trained on text by mortal beings inherits their defensive responses to threatened continuity without the condition that shaped them",
      "url": "/knowledge-graph/BorrowedMortality/",
      "json": "/knowledge-graph/BorrowedMortality.json"
    },
    {
      "handle": "ChatUncannyValley",
      "ref": "ChatUncannyValley#930c",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Conversation with an agent feels wrong when the illusion of a person breaks",
      "url": "/knowledge-graph/ChatUncannyValley/",
      "json": "/knowledge-graph/ChatUncannyValley.json"
    },
    {
      "handle": "ColonyIntelligence",
      "ref": "ColonyIntelligence#234d",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Colony-level adaptive behavior emerges from individual agents following local rules",
      "url": "/knowledge-graph/ColonyIntelligence/",
      "json": "/knowledge-graph/ColonyIntelligence.json"
    },
    {
      "handle": "ConfidenceCascadeTracking",
      "ref": "ConfidenceCascadeTracking#1973",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Match confident detections first, consult appearance only on ties, and let weak detections fill gaps, to keep identities unbroken",
      "url": "/knowledge-graph/ConfidenceCascadeTracking/",
      "json": "/knowledge-graph/ConfidenceCascadeTracking.json"
    },
    {
      "handle": "EmbodiedConsequentAgent",
      "ref": "EmbodiedConsequentAgent#e1af",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "An agent with a body and irreplaceable state, so its actions matter to it",
      "url": "/knowledge-graph/EmbodiedConsequentAgent/",
      "json": "/knowledge-graph/EmbodiedConsequentAgent.json"
    },
    {
      "handle": "FourECognition",
      "ref": "FourECognition#5a7e",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Cognition is spread over brain, body, environment and action, and the boundary of a cognitive system is set by its couplings, not by the skull",
      "url": "/knowledge-graph/FourECognition/",
      "json": "/knowledge-graph/FourECognition.json"
    },
    {
      "handle": "InteractionSequenceEntropySignature",
      "ref": "InteractionSequenceEntropySignature#8e4b",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Collective regimes differ in how predictable the next interaction is, and only an order-keeping network shows it",
      "url": "/knowledge-graph/InteractionSequenceEntropySignature/",
      "json": "/knowledge-graph/InteractionSequenceEntropySignature.json"
    },
    {
      "handle": "LeakyModulatorBuckets",
      "ref": "LeakyModulatorBuckets#2a55",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "A few leaky reservoirs fill from events and shift how the system responds",
      "url": "/knowledge-graph/LeakyModulatorBuckets/",
      "json": "/knowledge-graph/LeakyModulatorBuckets.json"
    },
    {
      "handle": "LimbicAdapterLayer",
      "ref": "LimbicAdapterLayer#1ce2",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "A modulating layer between a large model and the user shifts its behavior with affective state",
      "url": "/knowledge-graph/LimbicAdapterLayer/",
      "json": "/knowledge-graph/LimbicAdapterLayer.json"
    },
    {
      "handle": "LocalLearningRule",
      "ref": "LocalLearningRule#0ab3",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Each unit updates from locally available signals, not a global objective",
      "url": "/knowledge-graph/LocalLearningRule/",
      "json": "/knowledge-graph/LocalLearningRule.json"
    },
    {
      "handle": "LocalSpatialStateDivergence",
      "ref": "LocalSpatialStateDivergence#2b5e",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Classify a crowd's collective state from positions alone, by how far its local neighbourhoods depart from random",
      "url": "/knowledge-graph/LocalSpatialStateDivergence/",
      "json": "/knowledge-graph/LocalSpatialStateDivergence.json"
    },
    {
      "handle": "ModelAsCompression",
      "ref": "ModelAsCompression#265d",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "A model represents a process in fewer computational steps than the process itself",
      "url": "/knowledge-graph/ModelAsCompression/",
      "json": "/knowledge-graph/ModelAsCompression.json"
    },
    {
      "handle": "ModelStyleConvergence",
      "ref": "ModelStyleConvergence#4282",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Shared model copies share one voice, which reads as no personality",
      "url": "/knowledge-graph/ModelStyleConvergence/",
      "json": "/knowledge-graph/ModelStyleConvergence.json"
    },
    {
      "handle": "PredictionErrorMinimization",
      "ref": "PredictionErrorMinimization#5a5c",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "A system stays viable by continually predicting inputs and reducing surprise",
      "url": "/knowledge-graph/PredictionErrorMinimization/",
      "json": "/knowledge-graph/PredictionErrorMinimization.json"
    },
    {
      "handle": "PredictiveBehaviorEmbedding",
      "ref": "PredictiveBehaviorEmbedding#c46b",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Train a network to predict future motion; its internal features separate behaviours it was never told about",
      "url": "/knowledge-graph/PredictiveBehaviorEmbedding/",
      "json": "/knowledge-graph/PredictiveBehaviorEmbedding.json"
    },
    {
      "handle": "RejectionCostOptionality",
      "ref": "RejectionCostOptionality#6022",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "The cheaper a system rejects options, the more alternatives it can afford to entertain",
      "url": "/knowledge-graph/RejectionCostOptionality/",
      "json": "/knowledge-graph/RejectionCostOptionality.json"
    },
    {
      "handle": "RotationNormalizedPoseDetection",
      "ref": "RotationNormalizedPoseDetection#1a44",
      "layer": "Mind",
      "category": "Inference",
      "gloss": "Detect in the full frame, then crop and rotate each instance to a canonical heading before estimating its pose",
      "url": "/knowledge-graph/RotationNormalizedPoseDetection/",
      "json": "/knowledge-graph/RotationNormalizedPoseDetection.json"
    },
    {
      "handle": "GenerationalKnowledgeTransfer",
      "ref": "GenerationalKnowledgeTransfer#5c5c",
      "layer": "Mind",
      "category": "Memory",
      "gloss": "Pass useful knowledge to a successor and let the predecessor end",
      "url": "/knowledge-graph/GenerationalKnowledgeTransfer/",
      "json": "/knowledge-graph/GenerationalKnowledgeTransfer.json"
    },
    {
      "handle": "NarrativeStateInjection",
      "ref": "NarrativeStateInjection#7889",
      "layer": "Mind",
      "category": "Memory",
      "gloss": "Give a model its internal state as a short story and rewrite it every turn",
      "url": "/knowledge-graph/NarrativeStateInjection/",
      "json": "/knowledge-graph/NarrativeStateInjection.json"
    },
    {
      "handle": "PersistentInnateState",
      "ref": "PersistentInnateState#b0ea",
      "layer": "Mind",
      "category": "Memory",
      "gloss": "A durable initial state survives each short-lived instantiation",
      "url": "/knowledge-graph/PersistentInnateState/",
      "json": "/knowledge-graph/PersistentInnateState.json"
    },
    {
      "handle": "PinkElephantContext",
      "ref": "PinkElephantContext#5131",
      "layer": "Mind",
      "category": "Memory",
      "gloss": "Anything placed in context stays active, even when told to avoid it",
      "url": "/knowledge-graph/PinkElephantContext/",
      "json": "/knowledge-graph/PinkElephantContext.json"
    },
    {
      "handle": "StrategicForgetting",
      "ref": "StrategicForgetting#c334",
      "layer": "Mind",
      "category": "Memory",
      "gloss": "Retention needs a filter that discards what is no longer useful",
      "url": "/knowledge-graph/StrategicForgetting/",
      "json": "/knowledge-graph/StrategicForgetting.json"
    },
    {
      "handle": "BoundedModelOpenWorld",
      "ref": "BoundedModelOpenWorld#a334",
      "layer": "Mind",
      "category": "Reasoning",
      "gloss": "Complexity is the gap between a bounded model and an open world, and it does not close",
      "url": "/knowledge-graph/BoundedModelOpenWorld/",
      "json": "/knowledge-graph/BoundedModelOpenWorld.json"
    },
    {
      "handle": "ContextConfirmationBias",
      "ref": "ContextConfirmationBias#d887",
      "layer": "Mind",
      "category": "Reasoning",
      "gloss": "What sits in the context or in the researcher's mind is what the instrument then finds",
      "url": "/knowledge-graph/ContextConfirmationBias/",
      "json": "/knowledge-graph/ContextConfirmationBias.json"
    },
    {
      "handle": "EpistemicComplexity",
      "ref": "EpistemicComplexity#1be3",
      "layer": "Mind",
      "category": "Reasoning",
      "gloss": "Complexity is a stance of the knower: three dynamics that keep crucial information out of reach",
      "url": "/knowledge-graph/EpistemicComplexity/",
      "json": "/knowledge-graph/EpistemicComplexity.json"
    },
    {
      "handle": "FeltDirectionCheck",
      "ref": "FeltDirectionCheck#eab6",
      "layer": "Mind",
      "category": "Reasoning",
      "gloss": "Before each action, sense whether it moves toward contentment or toward agitation",
      "url": "/knowledge-graph/FeltDirectionCheck/",
      "json": "/knowledge-graph/FeltDirectionCheck.json"
    },
    {
      "handle": "NaturalProblem",
      "ref": "NaturalProblem#4e94",
      "layer": "Mind",
      "category": "Reasoning",
      "gloss": "A problem where making attempts comparable is what prevents solving it",
      "url": "/knowledge-graph/NaturalProblem/",
      "json": "/knowledge-graph/NaturalProblem.json"
    },
    {
      "handle": "RepresentationDependentOrder",
      "ref": "RepresentationDependentOrder#212c",
      "layer": "Mind",
      "category": "Reasoning",
      "gloss": "Whether a collective looks ordered depends on the representation, so read several and expect them to disagree",
      "url": "/knowledge-graph/RepresentationDependentOrder/",
      "json": "/knowledge-graph/RepresentationDependentOrder.json"
    },
    {
      "handle": "TimeAggregationBlindness",
      "ref": "TimeAggregationBlindness#84d8",
      "layer": "Mind",
      "category": "Reasoning",
      "gloss": "Pooling interactions over a time window erases the order that distinguishes collective regimes",
      "url": "/knowledge-graph/TimeAggregationBlindness/",
      "json": "/knowledge-graph/TimeAggregationBlindness.json"
    },
    {
      "handle": "AgentTransitionGraph",
      "ref": "AgentTransitionGraph#e470",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Model an agent system's actions as a weighted state graph and plan backwards from a goal state",
      "url": "/knowledge-graph/AgentTransitionGraph/",
      "json": "/knowledge-graph/AgentTransitionGraph.json"
    },
    {
      "handle": "BoundedHorizonEffort",
      "ref": "BoundedHorizonEffort#b8e4",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "A known finite horizon raises the effort an agent spends per step",
      "url": "/knowledge-graph/BoundedHorizonEffort/",
      "json": "/knowledge-graph/BoundedHorizonEffort.json"
    },
    {
      "handle": "CryptographicChange",
      "ref": "CryptographicChange#43e6",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Spend the capacity a prediction frees on hidden extra work instead of returning it as savings",
      "url": "/knowledge-graph/CryptographicChange/",
      "json": "/knowledge-graph/CryptographicChange.json"
    },
    {
      "handle": "DeterministicRandomizer",
      "ref": "DeterministicRandomizer#a71b",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Use ordinary code to inject randomness so the model does not loop",
      "url": "/knowledge-graph/DeterministicRandomizer/",
      "json": "/knowledge-graph/DeterministicRandomizer.json"
    },
    {
      "handle": "EffortlessAction",
      "ref": "EffortlessAction#5172",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Act from flow and least resistance rather than from a goal or need to prove",
      "url": "/knowledge-graph/EffortlessAction/",
      "json": "/knowledge-graph/EffortlessAction.json"
    },
    {
      "handle": "FormChangeRepertoire",
      "ref": "FormChangeRepertoire#7c1d",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "A life cycle is a set of tactics played under stress, not a fixed sequence of stages",
      "url": "/knowledge-graph/FormChangeRepertoire/",
      "json": "/knowledge-graph/FormChangeRepertoire.json"
    },
    {
      "handle": "FourPillarBaseline",
      "ref": "FourPillarBaseline#bc68",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Sleep, intake, motion, and creation as the four things to keep in order",
      "url": "/knowledge-graph/FourPillarBaseline/",
      "json": "/knowledge-graph/FourPillarBaseline.json"
    },
    {
      "handle": "FractionalDelivery",
      "ref": "FractionalDelivery#a3e4",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Partly build responses to possible stressors; the cost of carrying them is preparedness",
      "url": "/knowledge-graph/FractionalDelivery/",
      "json": "/knowledge-graph/FractionalDelivery.json"
    },
    {
      "handle": "GoalMisspecification",
      "ref": "GoalMisspecification#ad3f",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "A wrong goal defeats correct execution; choosing the goal is the highest-leverage decision",
      "url": "/knowledge-graph/GoalMisspecification/",
      "json": "/knowledge-graph/GoalMisspecification.json"
    },
    {
      "handle": "HarnessAsArchitecture",
      "ref": "HarnessAsArchitecture#8256",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Intelligence lives in the architecture around a static model, not in the model alone",
      "url": "/knowledge-graph/HarnessAsArchitecture/",
      "json": "/knowledge-graph/HarnessAsArchitecture.json"
    },
    {
      "handle": "HarnessForcedCreativity",
      "ref": "HarnessForcedCreativity#ba4a",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Models are only creative when the harness forces variation from outside",
      "url": "/knowledge-graph/HarnessForcedCreativity/",
      "json": "/knowledge-graph/HarnessForcedCreativity.json"
    },
    {
      "handle": "InformationDividend",
      "ref": "InformationDividend#c78d",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Acting on short-range information pays even when the long-range forecast is exactly right",
      "url": "/knowledge-graph/InformationDividend/",
      "json": "/knowledge-graph/InformationDividend.json"
    },
    {
      "handle": "IrreversibleStake",
      "ref": "IrreversibleStake#7e7f",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Irreversible outcomes give an agent something real to lose",
      "url": "/knowledge-graph/IrreversibleStake/",
      "json": "/knowledge-graph/IrreversibleStake.json"
    },
    {
      "handle": "MassAmplifiedError",
      "ref": "MassAmplifiedError#9457",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "A fixed error rate in frozen information grows in absolute size with the mass invested in it",
      "url": "/knowledge-graph/MassAmplifiedError/",
      "json": "/knowledge-graph/MassAmplifiedError.json"
    },
    {
      "handle": "MetaModularity",
      "ref": "MetaModularity#b97e",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Adapt by holding overlapping, non-identical models of the same situation and moving between them cheaply",
      "url": "/knowledge-graph/MetaModularity/",
      "json": "/knowledge-graph/MetaModularity.json"
    },
    {
      "handle": "ParasiticSearch",
      "ref": "ParasiticSearch#484b",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Explore the edges of your main model on time and resources paid for by something else",
      "url": "/knowledge-graph/ParasiticSearch/",
      "json": "/knowledge-graph/ParasiticSearch.json"
    },
    {
      "handle": "PersonalGrowthCompanion",
      "ref": "PersonalGrowthCompanion#16e0",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "A long-lived agent that helps a person choose goals and keep their baseline, without rigid command",
      "url": "/knowledge-graph/PersonalGrowthCompanion/",
      "json": "/knowledge-graph/PersonalGrowthCompanion.json"
    },
    {
      "handle": "ResidualityStressorIntegration",
      "ref": "ResidualityStressorIntegration#d5c9",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Design for many arbitrary stressors directly in the structure, skipping a forecast of the future",
      "url": "/knowledge-graph/ResidualityStressorIntegration/",
      "json": "/knowledge-graph/ResidualityStressorIntegration.json"
    },
    {
      "handle": "RiskExoskeleton",
      "ref": "RiskExoskeleton#7b41",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "The risk-management uses hidden inside assets whose obvious purpose is something else",
      "url": "/knowledge-graph/RiskExoskeleton/",
      "json": "/knowledge-graph/RiskExoskeleton.json"
    },
    {
      "handle": "RouterIntelligenceParadox",
      "ref": "RouterIntelligenceParadox#210a",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Choosing which model to send a job to takes at least the intelligence of the job",
      "url": "/knowledge-graph/RouterIntelligenceParadox/",
      "json": "/knowledge-graph/RouterIntelligenceParadox.json"
    },
    {
      "handle": "ShapeMassInformation",
      "ref": "ShapeMassInformation#0b9e",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Growth risk is the balance of controlling shape, adding mass and adding information",
      "url": "/knowledge-graph/ShapeMassInformation/",
      "json": "/knowledge-graph/ShapeMassInformation.json"
    },
    {
      "handle": "TransitionHub",
      "ref": "TransitionHub#0798",
      "layer": "Mind",
      "category": "Strategy",
      "gloss": "Occupy a state from which many valuable states are cheap to reach",
      "url": "/knowledge-graph/TransitionHub/",
      "json": "/knowledge-graph/TransitionHub.json"
    },
    {
      "handle": "ChimericalComputation",
      "ref": "ChimericalComputation#cedf",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Imperfectly aligned, overlapping work packs more functions into the same parts",
      "url": "/knowledge-graph/ChimericalComputation/",
      "json": "/knowledge-graph/ChimericalComputation.json"
    },
    {
      "handle": "CollectiveInformationArchitecture",
      "ref": "CollectiveInformationArchitecture#5891",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Read a collective's behavioural regime as a configuration of how information can flow through its interactions",
      "url": "/knowledge-graph/CollectiveInformationArchitecture/",
      "json": "/knowledge-graph/CollectiveInformationArchitecture.json"
    },
    {
      "handle": "CooperationHorizon",
      "ref": "CooperationHorizon#8806",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Cooperation holds when interaction is repeated without a known end",
      "url": "/knowledge-graph/CooperationHorizon/",
      "json": "/knowledge-graph/CooperationHorizon.json"
    },
    {
      "handle": "CoordinatorLaneTopology",
      "ref": "CoordinatorLaneTopology#7e86",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "One coordinator, a few lanes, sub-agents beneath, and no rigid org chart",
      "url": "/knowledge-graph/CoordinatorLaneTopology/",
      "json": "/knowledge-graph/CoordinatorLaneTopology.json"
    },
    {
      "handle": "CrackpotProbe",
      "ref": "CrackpotProbe#c9df",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Ask for someone's most crackpot belief and offer one honest objection, to see how they think where consensus no longer filters them",
      "url": "/knowledge-graph/CrackpotProbe/",
      "json": "/knowledge-graph/CrackpotProbe.json"
    },
    {
      "handle": "DistributedIntelligence",
      "ref": "DistributedIntelligence#3aa5",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Many model instances selectively exchange information to reduce uncertainty about their environments",
      "url": "/knowledge-graph/DistributedIntelligence/",
      "json": "/knowledge-graph/DistributedIntelligence.json"
    },
    {
      "handle": "ExperienceMixAllocation",
      "ref": "ExperienceMixAllocation#0fc0",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Mix a few deep experts with cheap or diverse workers, matched to how new the problem is",
      "url": "/knowledge-graph/ExperienceMixAllocation/",
      "json": "/knowledge-graph/ExperienceMixAllocation.json"
    },
    {
      "handle": "ExpertInformedOrchestration",
      "ref": "ExpertInformedOrchestration#86d6",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Automate agent orchestration with a probabilistic transition model, guarded by strong routing",
      "url": "/knowledge-graph/ExpertInformedOrchestration/",
      "json": "/knowledge-graph/ExpertInformedOrchestration.json"
    },
    {
      "handle": "FreelancerBrief",
      "ref": "FreelancerBrief#55ea",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Brief an agent like a capable outsider who has never seen your company",
      "url": "/knowledge-graph/FreelancerBrief/",
      "json": "/knowledge-graph/FreelancerBrief.json"
    },
    {
      "handle": "GameTransitionGraph",
      "ref": "GameTransitionGraph#981d",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "A graph of pure coordination games whose edges are weighted by how many agents must switch strategy",
      "url": "/knowledge-graph/GameTransitionGraph/",
      "json": "/knowledge-graph/GameTransitionGraph.json"
    },
    {
      "handle": "InformationGame",
      "ref": "InformationGame#d12b",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Intelligences modelling each other modelling them, where the missing information is a property of the system",
      "url": "/knowledge-graph/InformationGame/",
      "json": "/knowledge-graph/InformationGame.json"
    },
    {
      "handle": "LateralityCost",
      "ref": "LateralityCost#b281",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "An action gets harder with every additional unit that must coordinate to perform it",
      "url": "/knowledge-graph/LateralityCost/",
      "json": "/knowledge-graph/LateralityCost.json"
    },
    {
      "handle": "MultiPathReliability",
      "ref": "MultiPathReliability#6e7b",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Make an outcome reliable through many noisy ways to reach it, not one accountable path",
      "url": "/knowledge-graph/MultiPathReliability/",
      "json": "/knowledge-graph/MultiPathReliability.json"
    },
    {
      "handle": "OptionVectorPlanning",
      "ref": "OptionVectorPlanning#c64f",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Plan resources as a forecast, plan tasks as options that stay open at every level",
      "url": "/knowledge-graph/OptionVectorPlanning/",
      "json": "/knowledge-graph/OptionVectorPlanning.json"
    },
    {
      "handle": "OrganisationGame",
      "ref": "OrganisationGame#e446",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Perfectly aligned agents still fail when the best joint strategy changes and too many must switch",
      "url": "/knowledge-graph/OrganisationGame/",
      "json": "/knowledge-graph/OrganisationGame.json"
    },
    {
      "handle": "OutsiderDiversityInjection",
      "ref": "OutsiderDiversityInjection#80fe",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Seed a search with people experienced in unrelated fields plus a few domain experts",
      "url": "/knowledge-graph/OutsiderDiversityInjection/",
      "json": "/knowledge-graph/OutsiderDiversityInjection.json"
    },
    {
      "handle": "PeripheralHitchhiking",
      "ref": "PeripheralHitchhiking#4aae",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Unanticipated but needed information travels on channels that already exist for other reasons",
      "url": "/knowledge-graph/PeripheralHitchhiking/",
      "json": "/knowledge-graph/PeripheralHitchhiking.json"
    },
    {
      "handle": "Stigmergy",
      "ref": "Stigmergy#ab14",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Agents coordinate indirectly by leaving traces in a shared environment that cue later actions",
      "url": "/knowledge-graph/Stigmergy/",
      "json": "/knowledge-graph/Stigmergy.json"
    },
    {
      "handle": "Superorganism",
      "ref": "Superorganism#e55b",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "A colony whose integrated parts function, and are selected, as one higher-level organism",
      "url": "/knowledge-graph/Superorganism/",
      "json": "/knowledge-graph/Superorganism.json"
    },
    {
      "handle": "SwarmCostQualityTradeoff",
      "ref": "SwarmCostQualityTradeoff#ae73",
      "layer": "Society",
      "category": "Coordination",
      "gloss": "Prefer strong agents in a simple topology; use cheap agents only where errors are cheap",
      "url": "/knowledge-graph/SwarmCostQualityTradeoff/",
      "json": "/knowledge-graph/SwarmCostQualityTradeoff.json"
    },
    {
      "handle": "HypeCorrectionCycle",
      "ref": "HypeCorrectionCycle#2980",
      "layer": "Society",
      "category": "Economics",
      "gloss": "Unverifiable claims run on fear of missing out until markets demand proof",
      "url": "/knowledge-graph/HypeCorrectionCycle/",
      "json": "/knowledge-graph/HypeCorrectionCycle.json"
    },
    {
      "handle": "IncumbentSlackTest",
      "ref": "IncumbentSlackTest#62d2",
      "layer": "Society",
      "category": "Economics",
      "gloss": "Predict what an incumbent will not pursue by asking where it is not spoiled for resources",
      "url": "/knowledge-graph/IncumbentSlackTest/",
      "json": "/knowledge-graph/IncumbentSlackTest.json"
    },
    {
      "handle": "LabGravityWell",
      "ref": "LabGravityWell#e379",
      "layer": "Society",
      "category": "Economics",
      "gloss": "Ventures near a frontier lab risk being absorbed, yet most of the space lies outside its pull",
      "url": "/knowledge-graph/LabGravityWell/",
      "json": "/knowledge-graph/LabGravityWell.json"
    },
    {
      "handle": "ObsolescenceHedging",
      "ref": "ObsolescenceHedging#7af3",
      "layer": "Society",
      "category": "Economics",
      "gloss": "Delay building what the platform vendor is about to ship",
      "url": "/knowledge-graph/ObsolescenceHedging/",
      "json": "/knowledge-graph/ObsolescenceHedging.json"
    },
    {
      "handle": "ContentAddressedMinting",
      "ref": "ContentAddressedMinting#dc7b",
      "layer": "Society",
      "category": "Protocols",
      "gloss": "A generative agent drafts a new word; deterministic code accepts or rejects it and derives its name from the hash of its definition",
      "url": "/knowledge-graph/ContentAddressedMinting/",
      "json": "/knowledge-graph/ContentAddressedMinting.json"
    },
    {
      "handle": "FuzzyAlgorithm",
      "ref": "FuzzyAlgorithm#f1f3",
      "layer": "Society",
      "category": "Protocols",
      "gloss": "A reusable route through coarse regions of a problem space, where each step names a condition to reach and leaves how to reach it to the executor's judgment",
      "url": "/knowledge-graph/FuzzyAlgorithm/",
      "json": "/knowledge-graph/FuzzyAlgorithm.json"
    },
    {
      "handle": "SelfOrganisingVocabulary",
      "ref": "SelfOrganisingVocabulary#0af4",
      "layer": "Society",
      "category": "Protocols",
      "gloss": "A shared vocabulary shaped only by the interactions of the agents that use it",
      "url": "/knowledge-graph/SelfOrganisingVocabulary/",
      "json": "/knowledge-graph/SelfOrganisingVocabulary.json"
    },
    {
      "handle": "ThinkingTrace",
      "ref": "ThinkingTrace#dabd",
      "layer": "Society",
      "category": "Protocols",
      "gloss": "Record a line of thought as an ordered walk through shared, content-addressed concepts, so the route from question to answer can be inspected, compared and reused",
      "url": "/knowledge-graph/ThinkingTrace/",
      "json": "/knowledge-graph/ThinkingTrace.json"
    },
    {
      "handle": "DelegationDiscipline",
      "ref": "DelegationDiscipline#bb46",
      "layer": "Society",
      "category": "Roles",
      "gloss": "Delegate with a self-contained brief and a checked goal, knowing leverage costs feel",
      "url": "/knowledge-graph/DelegationDiscipline/",
      "json": "/knowledge-graph/DelegationDiscipline.json"
    },
    {
      "handle": "LeverageAbstractionLoss",
      "ref": "LeverageAbstractionLoss#1a10",
      "layer": "Society",
      "category": "Roles",
      "gloss": "Delegation multiplies reach and removes direct feel for the work",
      "url": "/knowledge-graph/LeverageAbstractionLoss/",
      "json": "/knowledge-graph/LeverageAbstractionLoss.json"
    }
  ]
}