Research axes

The six axes

Spaces say what is investigated. The research axes say which fundamental phenomena and capabilities are investigated across these objects. Each axis runs through several spaces.

1. 1

   Emergent Intelligencefoundational

   EIL investigates under which conditions intelligent structure, capabilities, strategies or coordination arise from repeated interaction between humans, models, agents, memory structures and technical systems.

   EIL investigates emergence in the broader sense: structures and patterns that arise from interaction. Emergent Intelligence is a specific perspective within this interest. It asks when intelligent structure, capabilities, strategies or coordination arise from it. Emergent Intelligence must not be reduced to the space Emergence, Adaptation & Complex Dynamics. On every space page where it is relevant, the connection must be visible.

   intelligent structure · capabilities · strategies · coordination · repeated interaction · stabilization

   Acts in the spaces: Emergent Intelligence

   Emergent Intelligence

   ×

   • A Human–AI Interaction & Co-EvolutionNew interaction regimes, new roles and co-adaptation between human and AI.
   • B Human Cognition, Behavior & ExternalizationEmergent Cognitive Architecture: new working practices and strategies arise from repeated work with the model.
   • C Emergence, Adaptation & Complex DynamicsEmergence detection, stabilization and the formation of new system structure.
   • D Reconstruction, Perspective & World ModelsEmergent internal models and new relations between models.
   • E Distributed, Agentic & Collective IntelligenceCollective intelligence, emergent specialization and emergent coordination.
   • F Computational Interaction & Cognitive ModelingDetection of emergent patterns through Recurrence Detection and Transition Analysis.
   • G Human–Machine Interfaces & Neuroadaptive SystemsEmergent control loops between human and system.
   • H Measurement, Evidence & Research InfrastructureOperationalization of emergence and the evidence for it.
2. 2

   Prediction & Behavioral Intelligencefoundational

   How behavior, structure, state changes and future consequences of action can be inferred from observable patterns, relational structures, constraints and temporal dynamics.

   In EIL prediction covers statistics and forecasting as well as structural reasoning: deriving possible next developments from actors, relations, constraints, behavior, states and dynamics.

   behavioral pattern recognition · actor modeling · state estimation · trajectory reconstruction · structural prediction · scenario reasoning · next-state prediction · decision prediction · constraint-based prediction · causal prediction

   Acts in the spaces: Prediction & Behavioral Intelligence

   Prediction & Behavioral Intelligence

   ×

   • A Human–AI Interaction & Co-EvolutionRecurring interaction patterns allow inferences about behavior and the next states of the relationship.
   • B Human Cognition, Behavior & ExternalizationBehavioral Intelligence: inferring a person's decisions and behavior from observable practice. Prediction is itself part of cognitive practice.
   • C Emergence, Adaptation & Complex DynamicsPredicting which patterns stabilize, and detecting state transitions.
   • D Reconstruction, Perspective & World ModelsTestable predictions from reconstructed state, actor structure, constraints and causal relations.
   • F Computational Interaction & Cognitive ModelingModeling of state transitions and trajectories as the basis for next-state and decision prediction.
3. 3

   Adversarial Thinking & Epistemic Integrityfoundational

   Systematic search for alternative explanations, contradictions, hidden assumptions, failure modes, manipulation, drift and faulty conclusions.

   This axis tests explanations from all other axes. It asks which assumptions they rest on and which alternatives they exclude, without any finding being confirmed by that alone.

   adversarial testing · counter-hypotheses · contradiction detection · failure analysis · semantic integrity · epistemic integrity · red teaming · assumption testing · unknown-state preservation · uncertainty calibration

   Acts in the spaces: Adversarial Thinking & Epistemic Integrity

   Adversarial Thinking & Epistemic Integrity

   ×

   • A Human–AI Interaction & Co-EvolutionSemantic repair and trust calibration.
   • D Reconstruction, Perspective & World ModelsCounter-hypotheses and alternative causal models.
   • E Distributed, Agentic & Collective IntelligenceAgent failure, drift and hidden centralization.
   • F Computational Interaction & Cognitive ModelingAnomaly detection and regression detection.
   • H Measurement, Evidence & Research InfrastructureInstrument drift, false state and evidence integrity.
4. 4

   Externalization & Reintegrationfoundational

   The cycle in which human cognitive practice becomes observable, formalized, externalized, computationally represented and integrated back into practice as a method, model, agent or system.

   The cycle must be visible as the connection between human cognition, computational modeling, agentic systems and measurement. Here lies the explanation of why EIL builds its own systems: the systems are partly research tools and at the same time results of earlier externalization processes.

   1. human cognitive practice
   2. observable repeated pattern
   3. formalization
   4. externalization
   5. computational representation
   6. method / model / agent / system
   7. reintegration
   8. changed future practice
   9. new externalization

   The cycle closes: the new externalization starts again at step 1. To the research cycle →

   The loop in long form (9 nodes) Concept

   1. 1Human cognitive practice
   2. 2Persistent human–AI interaction
   3. 3Observable recurring pattern
   4. 4Cognitive operation or heuristic
   5. 5Externalization
   6. 6Computational representation
   7. 7Reintegration into the human–AI workflow
   8. 8Observable change in later practice
   9. 9Next externalization cycle

   ↺ The ninth node leads back to the first.

   Acts in the spaces: Externalization & Reintegration

   Externalization & Reintegration

   ×

   • A Human–AI Interaction & Co-EvolutionReintegrated structures change the next interaction and the role of the AI.
   • B Human Cognition, Behavior & ExternalizationRecurring cognitive practice becomes observable, explicit and formalized: the starting point of the cycle.
   • E Distributed, Agentic & Collective IntelligenceHuman working functions are represented externally as specialized agent functions.
   • F Computational Interaction & Cognitive ModelingComputational representation of externalized practice, from formalization to an executable model.
   • H Measurement, Evidence & Research InfrastructureThe origin and effect of externalized structures stay evidenced and traceable.
5. 5

   Longitudinal Interaction Dynamics

   Longitudinality is the precondition for observing change, recurrence, stabilization, drift and co-evolution at all.

   Whether a pattern stays stable or drifts can only be tested across several time scales. The axis therefore asks about the time window of each observation itself.

   turn · session · multi-session · days · weeks · months · years

   Acts in the spaces: Longitudinal Interaction Dynamics

   Longitudinal Interaction Dynamics

   ×

   • A Human–AI Interaction & Co-EvolutionTrajectories across sessions, weeks, months and years are the object of the space.
   • B Human Cognition, Behavior & ExternalizationChange of cognitive working practice over time.
   • C Emergence, Adaptation & Complex DynamicsRecurrence, stabilization and drift only show over time.
   • D Reconstruction, Perspective & World ModelsTemporal reconstruction and history as part of the world model.
   • E Distributed, Agentic & Collective IntelligenceAgent systems are observed across many runs.
   • H Measurement, Evidence & Research InfrastructureTime-aware measurement, change tracking and datasets over long periods.
6. 6

   State, Memory & Continuity

   How state, memory and identity of human, model, agent and system stay coherent across sessions, restarts and years, and where continuity is only apparent.

   Whether continuity exists requires evidence. That a system reproduces earlier content does not, by itself, establish a stable identity or a correctly preserved state.

   human interaction state · model state · agent state · system state · memory · identity · continuity · false continuity · state divergence · state recovery

   Acts in the spaces: State, Memory & Continuity

   State, Memory & Continuity

   ×

   • A Human–AI Interaction & Co-EvolutionContinuity across sessions and restoring semantic continuity.
   • C Emergence, Adaptation & Complex DynamicsState-dependent behavior and state transitions.
   • E Distributed, Agentic & Collective IntelligenceAgent state, agent identity, state divergence and recovery.
   • F Computational Interaction & Cognitive ModelingState Reconstruction and State Estimation as computational state representation.
   • H Measurement, Evidence & Research InfrastructureState and memory infrastructure with safeguards against false continuity and false state.