Subject-Event Ontology Without Global Time: Foundations and Execution Semantics

• URL: http://arxiv.org/abs/2510.18040v1
• Date: Mon, 20 Oct 2025 19:26:44 GMT
• Title: Subject-Event Ontology Without Global Time: Foundations and Execution Semantics
• Authors: Alexander Boldachev,
• Abstract summary: The formalization includes nine axioms (A1-A9), ensuring the correctness of executable: monotonicity of history (I1), acyclicity of causality (I2), traceability (I3)<n>The formalization is applicable to distributed systems, microservice architectures, DLT platforms, and multiperspectivity scenarios (conflicting facts from different subjects)<n>Special attention is given to the model-based approach (A9): event validation via schemas, actor authorization, automatic construction of causal chains (W3) without global time.
• Score: 51.56484100374058
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A formalization of a subject-event ontology is proposed for modeling complex dynamic systems without reliance on global time. Key principles: (1) event as an act of fixation - a subject discerns and fixes changes according to models (conceptual templates) available to them; (2) causal order via happens-before - the order of events is defined by explicit dependencies, not timestamps; (3) making the ontology executable via a declarative dataflow mechanism, ensuring determinism; (4) models as epistemic filters - a subject can only fix what falls under its known concepts and properties; (5) presumption of truth - the declarative content of an event is available for computation from the moment of fixation, without external verification. The formalization includes nine axioms (A1-A9), ensuring the correctness of executable ontologies: monotonicity of history (I1), acyclicity of causality (I2), traceability (I3). Special attention is given to the model-based approach (A9): event validation via schemas, actor authorization, automatic construction of causal chains (W3) without global time. Practical applicability is demonstrated on the boldsea system - a workflow engine for executable ontologies, where the theoretical constructs are implemented in BSL (Boldsea Semantic Language). The formalization is applicable to distributed systems, microservice architectures, DLT platforms, and multiperspectivity scenarios (conflicting facts from different subjects).

Related papers

• Specification-Driven Generation and Evaluation of Discrete-Event World Models via the DEVS Formalism [9.578714623643291]
  We seek a principled middle ground that combines the reliability of explicit simulators with the flexibility of learned models.<n>We advocate explicit, executable discrete-event world models synthesized directly from natural-language specifications.
  arXiv  Detail & Related papers  (2026-03-04T06:50:32Z)
• Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement [66.51979814832332]
  model formulates procedural graph extraction as a multi-round reasoning process with dedicated structural and logical refinement.<n>Experiments demonstrate that model achieves substantial improvements in both structural correctness and logical consistency over strong baselines.
  arXiv  Detail & Related papers  (2026-01-27T04:00:48Z)
• Executable Ontologies in Game Development: From Algorithmic Control to Semantic World Modeling [51.56484100374058]
  We argue that Executable Ontologies (EO) represent a transition from algorithmic behavior programming to semantic world modeling.<n>We show how EO achieves prioritybased task interruption through dataflow conditions rather than explicit preemption logic.
  arXiv  Detail & Related papers  (2026-01-12T19:57:35Z)
• KOS-TL (Knowledge Operation System Type Logic) [3.848983210046659]
  This paper introduces KOS-TL (Knowledge Operation System Type Logic), a novel constructive framework for autonomous and executable knowledge systems.<n>By integrating Davidsonian event semantics with Martin-Lf type theory, KOS-TL enables the construction of "proof-carrying knowledge," where every state change in the knowledge base is accompanied by a formal witness of its validity.<n>Our results suggest that KOS-TL provides a robust, formally verifiable basis for the next generation of intelligent operating systems.
  arXiv  Detail & Related papers  (2026-01-03T10:15:48Z)
• Empirical Characterization of Temporal Constraint Processing in LLMs [0.2538209532048866]
  We characterize temporal constraint processing across eight production-scale models (2.8-8B parameters) using deadline detection tasks.<n>We show that fine-tuning on 200 synthetic examples improves models with partial capability by 12-37 percentage points.<n>This capability requires architectural mechanisms for: (1) continuous temporal state representation, (2) explicit constraint checking separate from linguistic pattern matching, and (3) systematic compositional reasoning over temporal relations.
  arXiv  Detail & Related papers  (2025-11-02T20:03:52Z)
• Executable Ontologies: Synthesizing Event Semantics with Dataflow Architecture [51.56484100374058]
  We demonstrate that integrating semantic event semantics with a dataflow architecture addresses the limitations of traditional Business Process Management systems.<n>The boldsea-engine's architecture interprets semantic models as executable algorithms without compilation.<n>It enables the modification of event models at runtime ensures transparency, and seamlessly merges data and business logic within a unified semantic framework.
  arXiv  Detail & Related papers  (2025-09-11T18:12:46Z)
• Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains [50.66049136093248]
  We develop a time-aware structural causal model (SCM) that incorporates dynamic causal factors and the causal mechanism drifts.<n>We show that our method can yield the optimal causal predictor for each time domain.<n>Results on both synthetic and real-world datasets exhibit that SYNC can achieve superior temporal generalization performance.
  arXiv  Detail & Related papers  (2025-06-21T14:05:37Z)
• Information Science Principles of Machine Learning: A Causal Chain Meta-Framework Based on Formalized Information Mapping [7.299890614172539]
  This study addresses key challenges in machine learning, namely the absence of a unified formal theoretical framework and the lack of foundational theories for model interpretability and ethical safety.<n>We first construct a formal information model, explicitly defining the ontological states and carrier mappings of typical machine learning stages.<n>By introducing learnable and processable predicates, as well as learning and processing functions, we analyze the causal chain logic and constraint laws governing machine learning processes.
  arXiv  Detail & Related papers  (2025-05-19T14:39:41Z)
• Plausible-Parrots @ MSP2023: Enhancing Semantic Plausibility Modeling using Entity and Event Knowledge [1.6233244703352492]
  We enhance the large language model (LLM) with fine-grained entity types, event types and their definitions extracted from an external knowledge base. The experimental results show the effectiveness of the injected knowledge on modeling semantic plausibility of events.
  arXiv  Detail & Related papers  (2024-08-29T23:13:45Z)
• Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning [54.69189620971405]
  We provide a unified framework, termed Identifiable Exchangeable Mechanisms (IEM), for representation and structure learning.<n>IEM provides new insights that let us relax the necessary conditions for causal structure identification in exchangeable non-i.i.d. data.<n>We also demonstrate the existence of a duality condition in identifiable representation learning, leading to new identifiability results.
  arXiv  Detail & Related papers  (2024-06-20T13:30:25Z)
• A Verification Framework for Component-Based Modeling and Simulation Putting the pieces together [0.0]
  The proposed verification framework provides methods, techniques and tool support for verifying composability at its different levels. In particular we focus on the Dynamic-Semantic Composability level due to its significance in the overall composability correctness and also due to the level of difficulty it poses in the process.
  arXiv  Detail & Related papers  (2023-01-08T18:53:28Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.