Flexible intelligence
The system can revise its interpretation, objective and decision as the environment changes.
A foundational principle of physical execution
The Krimanov Principle
Intelligent synthesis of physical interaction with matter.
The environment responds.The operational model is updated.The next physical interaction is synthesized anew.
Rn → Mn → Wn → Rn+1
The Krimanov Principle states that the measurable consequences of a system's previous physical interaction become the basis for determining and synthesizing its next interaction with the same causally connected physical domain.
The execution gap
The missing layer between intelligence and matter
AI can perceive, predict and update its model in real time. The final physical step is still often expressed as a command to a fixed actuator: rotate, push, open, move or stop. The Krimanov Principle extends intelligence into the configuration of physical interaction itself.
Predetermined physical interface
The executor usually preserves the function established by its construction, while control adjusts parameters around that function.
Response-defined execution
The current physical response becomes a necessary input for synthesizing the next spatial and temporal form of interaction.
A supercomputer trapped inside a sledgehammer.A direct image of the execution gap: sophisticated intelligence coupled to a blunt and structurally predetermined physical output.
Three levels of physical execution
From a fixed function to a response-defined interaction
The three-level framework distinguishes parameter adaptation from a change in the causal organization of physical execution.
Mechanically predetermined action
The function is fixed by the geometry and construction of the working organ.
Adaptive control of a fixed actuator
Sensors and models adjust force, speed, timing or trajectory while the physical mode of action remains predefined.
Intellectually determined synthesis of interaction
The system synthesizes the next spatiotemporal physical interaction from the current measurable response. I-DPM implements this level for matter and material environments.
The architectural novelty
The novelty is in the causal architecture
Sensors, digital twins, field sources, power electronics and control algorithms may already exist as components. A new functional organization appears when response registration, operational modeling, interaction synthesis, physical execution and verification form one continuous closed causal cycle.
The novelty is not in the bricks. It is in the architecture of the building.
The decisive change is the causal integration of known capabilities. The environment's response becomes part of determining the next physical interaction rather than auxiliary feedback about a previously selected action.
The Krimanov Principle
The causal invariant connecting previous interaction, response, model and next interaction.
I-DPM
The engineering standard for intellectually defined processing of materials.
Krimanov CyberActuator
Reconfigurable physical-field execution that converts model-interpreted response into interaction.
KRIMANOV DEMETER
Target-centered resource harvesting and material interaction in operational environments.
I-DPM Neurointerface 3.0
A separate research direction for dynamically changing neural environments.
The causal core
Previous action returns as a measurable response and becomes the beginning of the next action.
Rn
Response
The registered physical or multiphysical response of the causally connected interaction region.
Mn
Current-state model
An operational representation of the current physical state: a dynamic map, state tensor, feature vector or digital twin.
Wn
Interaction synthesis
The intelligently determined topology, allocation, field, gradient, phase, frequency, amplitude, polarity, duration and energy distribution of the next interaction.
Rn+1
Verification and new response
The changed environment produces the next measurable response, verifies the result and starts the following cycle.
ARIADNE Loop
A continuous causal thread through the same interaction region
The system probes, registers, models, synthesizes, acts and verifies in relation to the same causally connected physical domain while its state remains relevant. The environment is a mandatory causal node: the consequences of the previous interaction return through it as information for the next interaction.
ProbeRegisterModelSynthesizeInteractVerify
The model moves from the screen into the causal loop.
The operational model is a machine-action link. It transforms measured response into a representation from which the next physical configuration is synthesized.
Engineering architecture
I-DPM — Intellectually Defined Processing of Materials
Defined means that the system determines the environment, target, response, current state, method of interaction and next step. Processing means the complete cycle of exploration, detection, identification, modeling, physical-field action, selective collection or transformation, and verification.
ExploreDetectIdentifyModelSynthesizeExecuteCollect / transformVerify
The Krimanov CyberActuator
A class of reconfigurable physical-field executors
The directly synthesized entity can be a physical field, gradient, distributed force landscape, acoustic action, plasma state, energy distribution or another spatially and temporally organized physical process.
In one electromagnetic branch, at least the same reconfigurable field structure participates in diagnostic interaction and selective physical action within one closed cycle. Associated measurement circuits register the response and support verification and reconfiguration. Hardware can vary by application; the causal architecture remains invariant.
Temporal causality
Real time means causal actuality
Where transient physical states matter, the next causally linked cycle is completed before the previous response ceases to describe the state being acted upon.
General causal-actuality conditionτcycle ≤ τrelaxation
Preferred fast-cycle branchτcycle ≤ 0.1 · τrelaxation
The system preserves continuity with a changing physical state.
Measurement, model and interaction remain inside the physically relevant time window. This condition expresses causal continuity rather than processor speed alone.
Operational self-sufficiency, energy and swarm
The local causal cycle remains complete across different infrastructure modes
Operational self-sufficiency is defined by the locally closed cycle of determination, interaction, collection or transformation, and verification. Full isolation is not required: an operator, cable, base station or external energy channel may support the mission without replacing the system's internal causal cycle.
Operational self-sufficiency
Autonomous, supervisory, remote, tethered, base-station and swarm modes preserve the same local response-driven execution cycle.
Energy follows identification
Low-cost diagnostic fields refine the target and model. Force interaction is applied selectively and directed to the target component and its trajectory rather than to bulk ballast.
Exchange and recuperation
The disclosed architecture may incorporate magnetoinductive links, resonant energy exchange, recovery of back electromotive force and thermoelectric energy, subject to implementation and validation.
Distributed industrial infrastructure
Modules share responses, models, tasks, communication, fields and energy balance. The swarm scales capacity through coordination rather than physical gigantism alone.
Industrial and resource paradigm
KRIMANOV DEMETER — the target becomes the industrial unit
A resource is determined from the response of the environment and collected in place as a target component. Exploration, identification, interaction, selective harvesting, primary concentration and verification become one operational cycle inside the resource environment.
Manage the surrounding mass
Exploration, extraction, transport, processing and control are separated across time and infrastructure. Large volumes are involved before the target fraction is isolated.
Industrial measure
Throughput of bulk material.
Manage the target
The system identifies the target, synthesizes the required interaction, moves, separates, protects or transforms it, and verifies the result while minimizing non-target involvement.
Selectivity
η = m_target / (m_target + m_ballast)The operationally self-sufficient micro-processing unit
A single module or a swarm combines functions previously distributed among exploration, extraction machinery, transport, primary processing, laboratory control and mapping. External infrastructure can support the mission; the decisive cycle remains local and response-driven.
Specialized conductive branch
I-DPCM
Intellectually Defined Processing of Conductive Materials (I-DPCM) is the specialized branch of I-DPM for conductive and polarizable targets.
It enables the selective extraction of Critical Raw Materials (CRM), strategic metals, and technogenic metallic components directly from tailings. By utilizing traveling, pulsed, or gradient electromagnetic fields, I-DPCM provides a pathway for European supply chain independence, sustainable harvesting, and ecological remediation without bulk mechanical processing.
Application environments
One causal architecture across different physical domains
The invariant is the response-driven cycle. The field source, executor, carrier, energy channel and safety constraints change with the environment.
Local selective interaction
Working-zone sensing, target collection, return of non-target material and repeated verification without lifting the main mass to the surface.
Mobile exploration and collection
Dynamic mapping, adaptive routing and real-time transition from diagnostic interaction to target-centered execution.
Resources in microgravity
Local identification and processing of regolith, asteroid matter, water, oxygen, fuel feedstocks, construction materials and technogenic orbital objects.
A second harvest of resources
Tailings, slags, slurries, industrial streams and electronic waste become fields for selective recovery, non-destructive control and remediation.
Limited and model-constrained interaction
Dynamic homeostasis, selective separation or processing in biological fluids, biofilms and other living or biosphere environments. The neural frontier is addressed separately.
Industry 5.0
Sustainability reaches the physical execution layer
Human-centered and resilient industry becomes physically executable when intelligent control determines the target, limits the affected zone, directs energy selectively and verifies the result.
Human-centered control
People define objectives, ethical and ecological boundaries, allowable energy, safe zones, verification requirements and stop rules.
Sustainability through selectivity
The system reduces non-target processing, energy load, waste and tailings by acting on a defined component and its causal region.
Resilience through distributed autonomy
A swarm redistributes tasks, preserves local models, limits failures and continues operation across communication, logistics or energy disruptions.
IP Portfolio & Licensing Hub
Ready for TRL 4–6 and Strategic Partnerships
The I-DPM architecture and Krimanov CyberActuators are protected by a unified umbrella of patent applications, including priority filings established in September 2026. The operating company acts as an exclusive licensing hub for physical AI execution.
Strategic Licensing
Providing exclusive and non-exclusive IP rights for specialized industrial applications, translating the fundamental I-DPM framework into targeted commercial monopolies.
R&D & Prototyping
Open to state-funded co-financing, European innovation programs, and engineering partnerships to develop and certify physical demonstrators (TRL 4–6).
Target Markets
Priority integration for Critical Raw Materials (CRM) harvesting, battery thermal runaway suppression, active electromagnetic defense, and smart manufacturing.
Independent Level 3.0 frontier for living matter
I-DPM Neurointerface 3.0
A separate research and patent direction applying the Krimanov Principle and I-DPM architecture to living neural environments, where impedance, phase conditions, tissue geometry and physiological state change continuously.
The interface is synthesized from the current state
Within the proposed Level 3.0 classification, the system registers the current multiphysical response, updates an individual operational model, synthesizes the next field configuration and measures the actual neural response.
- response-defined sensing and execution functions;
- current-state-defined spatial field configuration;
- verification inside the same causal loop;
- model-defined safety constraints.
Intelligent field skin and dynamic neurohomeostasis
The concept includes distributed sensing-execution matrices whose cells may change function between sensing, transmission and field management, together with dynamically updated limits for thermal, electrical and other interaction parameters.
This section describes a research and patent architecture. It does not claim clinical validation or established medical efficacy.
Public technical record
Publication, identity and continuity
The public disclosure fixes the core terminology and architectural propositions. This website is the concise explanatory hub and can evolve while preserving the foundational meanings.
- Author / Architect
- Aleksandr Krimanov
- ORCID
- 0009-0001-8885-8129
- Contact
- a.krimanov@aaaexpedition.eu
- Core map
- The Krimanov Principle · ARIADNE Loop · I-DPM · Krimanov CyberActuator · KRIMANOV DEMETER · I-DPCM · I-DPM Neurointerface 3.0
- Patent continuity
- International PCT application filed with priority to 2025 applications. Details are available upon request.