This article develops Change Praxeology as a normative-metatheoretical architecture of action grounded in Change Ontology, Change Epistemology, and Change Axiology. Its primary thesis is that responsible action in continuous, multi-causal change is best understood as justified, proportionate, feedback-responsive, and withdrawable intervention in an event-flow already underway. The proposed architecture is P-J-I-M-E: Perceive, Judge, Intervene, Monitor, and Exit, followed by renewed perception under risk-proportionate attention. The paper distinguishes ontological premises from normative bridge premises, consolidates a technical lexicon, and narrows its novelty (...) claim through comparison with practical wisdom, planning theory, pragmatism, situated action, process philosophy, cybernetics, bounded rationality, adaptive management, and viability theory. Epistemic confidence may suspend substantive intervention; affected-party value and governing-boundary analysis determine whether a trajectory is viable; authorization constrains entry and exit; timing windows and reversible probes guide minimum sufficient intervention; and differentiated withdrawal supports completion, diagnosis, or emergency protection. Fixed endpoints are supplemented by dynamic corridors characterized by bounds, residence, excursion, recovery, and distributional integrity. A discriminating wellbeing case compares the framework with plan-execution and generic adaptive planning. Six defeasible hypotheses and a comparative research programme specify how the theory may be supported, revised, or rejected. ChangeCision AI is presented as an implementation research programme rather than empirical confirmation. The contribution is an integrated and testable account of action-flow within continuous change-flow. (shrink)

This article proposes Change Ontology as a structured framework for domains in which reality is better understood as continuous event-flow than as stable substance. Its central thesis is that change, rather than substance, state, or even process, should be treated as the primordial meta-fact in fluid domains: entities, states, and processes are derivative stabilizations or cognitive segmentations within ongoing change-flow. Substance-centered metaphysics remains valuable where identity, classification, and stable reference are required, but it becomes limited in domains marked by emergence, (...) transformation, instability, feedback, and continuous adaptation. The article introduces a seven-module model: Dao-De or Governing Logic-Governing Operation, Entity-Process, Spatial Dimension-Time and Order, Attribute-Dynamical System, Symbol-Development Trend, Three Views-Consciousness, and Change-Balance. These modules form a cognitive-action closed loop connecting boundary constraint, sensing, encoding, reasoning, decision, action, and feedback. The model is positioned against Substance Ontology, Process Ontology, Daoist and Chinese correlative thought, systems theory, cybernetics, and complexity thinking. It then applies the framework to personal well-being across eight dimensions and presents ChangeCision AI as a possible application architecture rather than as a completed or empirically validated system. The article concludes that Change Ontology should not be read as a replacement for existing ontologies, but as a supplementary event-flow framework for fluid, feedback-sensitive domains. (shrink)

This article proposes Change Axiology as a reconstruction of value theory grounded in Change Ontology and Change Epistemology. It argues that traditional axiology often begins from an implicit good-state assumption, treating value as if it were already oriented toward a desirable state, rule, outcome, or character. Change Axiology instead defines value as a neutral relation of matching between a change-event and a subject's orientation, intention, need, or sustainable continuation under specified conditions and scales. On this basis, good is not the (...) definition of value but one possible classification: high positive matching. The paper develops the concepts of value-flow, subject-environment-scale specification, governing boundary, convergence-divergence, and the value-action matrix. It positions Change Axiology in dialogue with utilitarianism, deontology, virtue ethics, pragmatism, value pluralism, and value-sensitive design, while arguing that dynamic, open, feedback-sensitive domains require an axiology capable of continuous monitoring and revision. The paper concludes by showing how Change Axiology bridges Change Epistemology and Change Praxeology and offers a philosophical foundation for adaptive AI value alignment and ChangeCision AI. (shrink)

This article proposes Change Epistemology as a framework for knowing in domains where reality is better understood as continuous change-flow than as a collection of static states. Traditional epistemology often evaluates knowledge through belief, truth, justification, evidence, and reliability, from the justified true belief tradition to reliabilist and virtue-theoretic accounts. These concerns remain indispensable, but they tend to privilege snapshot-like assessment: a proposition is judged against a state of affairs at a moment. Change Epistemology begins from Change Ontology, according to (...) which time cannot be stopped, change is the primordial meta-fact, and states are cross-sections of ongoing event-flow. On this basis, the article argues that knowledge in fluid domains should be understood not primarily as static true belief, but as the encoding, tracking, and updating of change-patterns and their associations. The paper develops five contributions. First, it defines the change-event and association rule as dynamic epistemic units. Second, it formalizes cognitive flow through timestamp, confidence, decay function, verification threshold, and re-check planning. Third, it reframes Gettier-style lucky truth as under-tested cognition rather than settled knowledge. Fourth, it distinguishes static knowledge, meaningful connection as intelligence, and valuable connection as wisdom. Fifth, it introduces viability as a boundary-aware epistemic-practical test: knowing in change-flow must ask whether a path is viable for whom or what, at whose cost, and within what governing boundaries. The article positions this proposal in relation to Gettier, Goldman, Nozick, Bayesian epistemology, dynamic epistemic logic, Dewey's pragmatism, Dretske's information flow, social epistemology, and virtue epistemology. It concludes that Change Epistemology does not abolish traditional epistemology, but supplements it for dynamic, open, feedback-sensitive domains. (shrink)

This article develops Change Philosophy as an integrated framework of ontology, epistemology, axiology, and praxeology. The experiential claim that time does not stop serves as an entry point rather than a deductive proof. Change is proposed, through a cumulative, abductive, and reconstructive argument, as the primordial meta-fact: concrete phenomena are interpreted as temporally and relationally conditioned formations, while relative stability is explained as patterned continuity within change. V2.2 sharpens the priority thesis by distinguishing universality from meta-factuality and by defining entity, (...) property, state, process, relation, and law as derived roles within event-flow. Failure of indispensable reconstruction would count against the strong mono-categorical thesis. Causation is bounded as a separate explanatory question except where a causal theory claims ontological priority. Dao is defined as the proposed governing law of sustainable continuity through convergence and divergence, and De as the standard of operation aligned with Dao. Within this hierarchy, Change Ontology interprets reality as event-flow; Change Epistemology treats knowing as time-indexed, confidence-sensitive cognitive flow; Change Axiology treats value as dynamic relevance and consequence for affected beings and systems; and Change Praxeology treats action as authorized, proportionate, monitored, and withdrawable intervention. Explicit bridge premises connect event-flow, cognitive flow, value-flow, action-flow, and renewed event-flow without deriving normative conclusions from ontology alone. The seven-module model is classified as a defeasible functional decomposition rather than an ontological proof, while P-J-I-M-E and a layered distributed ChangeCision AI architecture remain operational research programmes. Direct comparison with Aristotle, Whitehead, event ontology, persistence theory, structural realism, and powers ontology is joined by stronger objection-reply treatment concerning substrate, external stimulus, category dependence, and normativity. The contribution is configurational and conditional: an integrated and criticizable philosophy of continuous change whose standing must be established through rival comparison, domain study, and tests capable of revealing conceptual or practical failure. (shrink)

Change Logic is proposed as a dynamic logic for analysing change-flow rather than static propositions alone. It extends Change Philosophy by organizing reality, cognition, valuation, and action into four interrelated flows: event-flow, cognitive-flow, value-flow, and action-flow. Event-flow records what is changing through entity-process, spatial-temporal order, and dynamical attributes. Cognitive-flow interprets these changes through symbols, pattern recognition, and development trends. Value-flow evaluates the relevance, direction, and consequence of change through value orientation and consciousness. Action-flow governs intervention, adjustment, withdrawal, and feedback through (...) the logic of change-balance. The central claim of Change Logic is that many theoretical and practical errors arise when dynamic phenomena are forced into static conceptual forms. Traditional logic is powerful for formal consistency, but it often abstracts away timing, sequence, context, value conflict, feedback, and intervention. Change Logic therefore introduces a four-flow diagnostic method for identifying where a problem occurs: in the event itself, in cognition, in value interpretation, in action, or in the relation between these flows. This framework is applied to classical philosophical problems such as the is-ought gap, identity through change, the Gettier problem, induction, free will, and the problem of other minds, not by claiming final solutions, but by locating missing mediations, unclear objects, static assumptions, and broken logical transitions. Change Logic also provides a practical framework for artificial intelligence, wellbeing, organizational governance, education, public policy, and ethical intervention. Its governing boundary is Dao-De: the logic of sustainable continuity through convergence and divergence, and the operational alignment required for responsible action. By treating knowledge, value, and action as dynamic and revisable flows, Change Logic offers a structured method for reasoning under uncertainty, intervening with proportionality, withdrawing responsibly, and maintaining system confidence. It presents itself not as a replacement for formal logic, but as a complementary logic for a world in continuous change. (shrink)