A Novelty–Plausibility Recursive Framework for Creative Reasoning in Epistemic Idea-Spaces

We present an information-theoretic framework that models creative reasoning as structured, task-directed motion within hierarchically organized epistemic structures. Creative problem solving is described as a progressive reconfiguration of an initial epistemic state toward a desired target configuration through a sequence of intermediate representations. Each representation is modeled by an empirical structural distribution over extracted features, enabling two complementary quantitative diagnostics: (i) a divergence measure—the Jensen–Shannon (JS) metric—capturing structural departure, novelty, and analogical proximity; and (ii) energy-based plausibility measures expressing conformity to dominant structural regularities and agent-relative constraints. Their interaction induces a geometry in which exploration balances novelty against structural admissibility, and cross-domain transfer is enabled through alignment of compatible representations. We introduce algebraic and probabilistic principles governing the generation, evaluation, and selection of candidate representations, including neighborhood-restricted exploration, history-sensitive evaluation, and non-redundant comparison under progressively refined interpretive conditions. The framework is operationalized at the level of the epistemic structures accessible to an individual reasoning agent, while large language models are interpreted as mechanisms that facilitate access to broader reservoirs of structured knowledge. Although a musical case study (J. S. Bach’s The Art of Fugue) is used for illustration, the proposed framework is domain-general and applies to any setting involving structured representations and lawful transformations. The resulting formalism supports principled approaches to task-oriented creative search, analogical reasoning, and autonomous knowledge exploration, with potential implications for machine-assisted discovery and structurally grounded communication across intelligent systems.