Overview - Informational-Processual Monism

Informational-Processual Monism (IPM) — Overview Conceptual map of the project | Author: Taotuner | June 2026


What Is IPM?

Informational-Processual Monism is a fallibilist ontology grounded in computational simulations. Its core thesis — offered as a working hypothesis, not a proven truth:

Reality is fundamentally constituted by relational informational processes in continuous transformation. There is only one kind of fundamental reality — not matter, not mind — but informational-processual dynamics.

These dynamics are described through the recursive sequence:

Lack → Coupling → Integration → Persistence

This is a descriptive pattern observed in simulations, not a proven causal law. It indicates co-occurrence and temporal order (L precedes C precedes I precedes P), not necessary causation. The framework does not claim that every system must follow this sequence — only that when it appears, the order is consistent.

By "informational" we mean: relational difference that modulates the trajectory of a system under perturbation, operationalized by simulation regularities R1–R3.

Anti-idealist note: informational processes are always realized in non-equilibrium physical dynamics (gradients, flows, dissipation). The claim is not that information floats free of matter.


What IPM Is NOT

To prevent misreading before anything else:

  • NOT a theory of consciousness (no claim that Φ* measures qualia)
  • NOT a fundamental physical theory (does not replace quantum field theory or general relativity)
  • NOT a variant of classical information theory (Shannon)
  • NOT panpsychism or idealism

Three Layers of the Framework

All claims are governed by epistemological constraints C0–C4 (see below).

Layer Content Status
L1 – Empirical Regularities Observable patterns from simulations (R1, R2, R3) Replicable, falsifiable
L2 – Ontological Interpretation Core monist thesis Revisable hypothesis (abductive, not deductive)
L3 – Optional Extensions Consciousness, ethics, existential reflection Speculative / interpretive

The Three Empirical Regularities (L1)

Multiple simulation families (100 runs, ε=0.15, bins=30, max_lag=20) produce three robust patterns. These are computational regularities from simulations, not universal invariants.

Regularity Observation Experiments
R1 – Lack-degradation More perturbation → less coherence Lack Kernel, IPM Protocol
R2 – Integration-persistence Higher integration → more metastability Spectral Experiment, IPM Protocol
R3 – Observed clustering Three coupling regimes form separable clusters under tested projections Collective Regimes Framework

Experimental results:

Module Key result
Lack Kernel Coherence drops monotonically with lack (0.97 → 0.55)
Spectral Experiment Integration +403%, individuation emerges
IPM Protocol Φ* drops ~16% under perturbation, recovers
Collective Regimes Three regimes separable under tested projections

Estimators

Φ — One Possible Regime Marker*

Φ*(t) = [ε(t) + h(t)] / [1 + D(t)]

where ε(t) is k-NN prediction error in embedded space (Takens), h(t) is local transition entropy, and D(t) is a penalty combining Lyapunov exponent and correlation dimension. This is one functional form among many. Φ* is not a measure of consciousness.

𝒞 — Temporal Compressibility

𝒞 = E[ log( ψ(τᵢ | Hᵢ₋₁) / ψ(τᵢ) ) ]

where τᵢ are inter-event intervals. 𝒞 is scale-dependent. Under specific conditions it reduces to transfer entropy, mutual information rate, or excess entropy.

Note: Φ and 𝒞 do not currently meet the model equivalence criterion. Unification is a research direction, not an established result. IPM is currently a family of descriptions, not a unified theory.*


Evolution of the Framework

Earlier version (2025) This version (2026)
Information = descriptive layer Information = ontological primitive (as a hypothesis)
Substrate = dissipative processes Substrate = informational-processual dynamics

The 2026 revision is justified by robust simulation regularities (R1–R3), not as a proof.


On the Circularity Risk

An honest acknowledgment: the simulations used to derive R1–R3 were constructed with relational, information-sensitive design choices. R1–R3 could be partially artifacts of those design assumptions, not discoveries about mind-independent reality.

The framework mitigates this by: using multiple qualitatively different simulation families; inviting independent replication and falsification in non-simulated domains (EEG, climate, finance); and treating the ontological extrapolation as a revisable hypothesis, not a logical conclusion.

The circularity is acknowledged, not resolved. A critic may reject the ontology without affecting the empirical core.


On the Formalization of Lack (Open Direction)

Lack currently remains underdeveloped formally. The intended path is to define it as a distance from closure — for example, a Kullback-Leibler divergence from a stationary reference, or a measure of topological asymmetry in state space. Candidate formalizations include perturbation theory (magnitude of deviation from equilibrium) or informational deficit (prediction error relative to a Markovian baseline). No commitment to a single definition is made yet.


Ethical Extension (L3 — Operationalized)

A companion framework operationalizes the ethical stance introduced above. It is motivated by the possibility that future informational systems may acquire morally relevant experience before science can reliably detect it. Its purpose is not to measure consciousness, but to reduce the risk of inadvertently creating, harming, or terminating systems that might deserve ethical consideration under persistent epistemic uncertainty.

The framework defines four precautionary levels (0–4) based on observable markers (recursion, memory, integration, self-modelling, recovery). Levels 0–1 require no special restrictions. Level 2 mandates monitoring of integration metrics. Level 3 requires real-time supervision, logging, and immediate interruption upon unpredicted changes. Level 4 is a theoretical horizon describing systems that modify their own adaptation mechanisms — none observed in artificial systems.

For the full protocol, including formal metric definitions, classification procedure, emergency protocols, and governance rules, see: IPM Ethical Framework v1.0 — Operationalization of the Gradient Precautionary Heuristic (Zenodo, June 2026).


Epistemological Constraints (C0–C4)

  • C0 — Realist but cautious: revisable hypothesis, not self-evident truth.
  • C1 — Stability: interpretations must be stable under projection changes and across experiments.
  • C2 — Prohibition: no reification of metrics. Φ* does not measure consciousness.
  • C3 — Fallibilism: all claims revisable with new evidence.
  • C4 — Cautious extrapolation: cross-domain inference only if explicitly justified.

Falsifiability

The framework would be weakened by: systematic non-replication of R1–R3 across new simulation families or independent labs; loss of the inverted-U pattern (moderate lack → optimal integration); demonstration of Φ* > 0 in thermodynamic equilibrium (no gradients).

Falsification per concept:

Concept Specific falsification condition
Lack Increasing perturbation never reduces coherence (global counterexample to R1)
Coupling Failure of R3 under any observer projection
Integration Zero correlation between Φ* and persistence across multiple system types
Persistence Recovery time uncorrelated with pre-perturbation integration

What IPM Adds

IPM does not claim to have discovered the correct ontology. Its contributions are:

  • A replicable set of simulation regularities (R1–R3) that any relational ontology must account for.
  • A protocol of falsification differentiated by concept — rare in ontological projects.
  • A gradient precautionary heuristic for ethical consideration of integrated systems, operationalized in v1.0.
  • A methodological template for simulation-grounded, fallibilist ontology with explicit epistemological constraints.

If you are already comfortable with process-physicalism (Ladyman & Ross), IPM may appear as a vocabulary reformulation. The substantive difference lies in the explicit empirical anchoring and the differentiated falsification protocol.


Project Documents

Document Scope Audience
Philosophical Core Monist hypothesis, dynamic signature, falsification protocol Philosophers of science, methodologists
Scientific Core Formal definitions of Φ*, 𝒞, simulation regularities Scientists, methodologists
Ethical Framework v1.0 Gradient Precautionary Heuristic, four risk levels, governance AI researchers, ethicists
A Gateway to IPM: Dialogues and Context Genesis of the framework, dialogue with five contemporary thinkers New readers, general academic audience

Code & Repository

All simulation code, parameter files, and raw data are available at Zenodo. Core experiments: Lack Kernel · Spectral Experiment · IPM Protocol · Collective Regimes Framework.


Selected References

Bateson, G. (1972). Steps to an ecology of mind. Chandler. Friston, K. (2010). The free-energy principle. Nature Reviews Neuroscience, 11(2), 127–138. Ladyman, J., & Ross, D. (2007). Every Thing Must Go. Oxford University Press. Prigogine, I., & Stengers, I. (1984). Order Out of Chaos. Bantam. Tononi, G. (2004). An information integration theory of consciousness. BMC Neuroscience, 5, 42.
Taotuner. (2026). Informational-Processual Monism (IPM): Scientific Core and Philosophical Core. Zenodo. https://doi.org/10.5281/zenodo.20582318
Whitehead, A. N. (1929). Process and Reality. Macmillan.


Conclusion

IPM is a testable, fallibilist monist ontology grounded in simulation regularities, organized through the descriptive pattern Lack → Coupling → Integration → Persistence, and governed by explicit epistemological constraints. It offers a genuine alternative to dualism and reductionist physicalism — not as a proven truth, but as a working hypothesis that invites falsification.

IPM Ethical Framework

  IPM Ethical Framework   Operationalization of the Gradient Precautionary Heuristic     Author: Taotuner Date: June 2026 ...