Title: Change Epistemology: From Static True Belief to Dynamic Cognitive Flow

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.