Zero Tier Execution Substrate for Evolutionary Software Systems

Adaptive and evolutive software systems are characterized by ontologically defined non-determinism—not a defect but the primary force of their evolution. Non-determinism arises from recursion, interaction, and selection between abstract components and can only be resolved as the execution sequence grows sufficiently for one outcome to become determinate. In adaptive systems, managing this non-determinism through structural adaptation of abstract components during execution is the defining operational characteristic—one that no existing execution substrate formally supports. The problems of evolutive AI systems—inconsistency, non-reproducibility, absence of causal traceability, and an inability to enforce purpose-constrained autonomy—cannot be resolved within AI architectures alone. Resolving them requires a formal execution substrate in which causal context growth, resolution-moment detection, and structural adaptation of abstract components are first-class properties. This paper introduces the Zero Tier Execution Substrate (ZTES), grounded in a foundational model that defines execution as a sequence generated by recursive invocations of abstract components with ontologically specified purpose, in which non-determinism is resolved within the causal context of the sequence before commitment. ZTES is a homomorphic specification of this model, achieved through disciplined composition of the Mesarović–Takahara system ontology, Lamport-consistent causal ordering, P-DEVS transition semantics, and the Three-Phase execution kernel—mechanisms individually proven at a global scale. System execution is formally identified with the causal evolution of knowledge: Execution(Σ) ≡ Evolution(K). The historical knowledge base K has a two-dimensional orthogonal structure—the eschatological dimension encoding purpose lineage through recursive specialization, and the sequential dimension encoding event order through iterative mapping—which establishes purpose integrity as a substrate-level property of evolutive execution. The semantic closure of ZTES establishes deterministic reproducibility, governance–execution equivalence, and purpose-constrained autonomy as structural consequences of substrate closure rather than as additional architectural layers.