A formal theory on problem space as a semantic world model in systems engineering

arXiv 26.1 2026 40.7 method

TLDR

Formalizes problem space as a semantic world model in systems engineering with axioms and theorems for unambiguous boundary semantics.

Reasoning

The paper provides a rigorous theoretical formalization addressing a gap in systems engineering, but lacks empirical validation or real-world experiments; the hypothetical case study is illustrative only.

Read-first score

Read-first score 40.7, weighted from topical fit, citation, graph, method, reproducibility, and recency signals. Original total remains 9.

Recency 8%

100

Uses a gentle age decay so recent papers surface without erasing older foundations. 2026

Methodology quality 25%

Screens visible abstract and analysis fields for experiment, dataset, baseline, metric, and limitation evidence. markers=analysis,validation

Reproducibility 25%

Screens links and visible text for paper, code, dataset, artifact, and repository signals. pdf=True; code=False; dataset=False; markers=artifact

Topical relevance 42%

12.9

Uses existing LLM keyword relevance scores normalized to 0-100. world model,world simulator,generative world model,interactive world model,video world model,world dynamics prediction,model-based reinforcement learning world model

Field roles

FrontierMethodology anchor

Rank sensitivity

Stability: volatile; rank range: 470.

Keyword Scores

world model

world simulator

generative world model

interactive world model

video world model

world dynamics prediction

model-based reinforcement learning world model

Deep Analysis

Innovations

Formalization of problem space as an explicit semantic world model in systems engineering
Development of axioms, theorems, and corollary establishing rigorous criteria for boundary semantics, traceability, and sufficiency
Clear distinction between what is true of the problem domain and what is chosen as a solution

Methodology

The paper develops a formal theory using axioms, theorems, and corollary to define problem space constructs. It then presents a dialogue-based hypothetical case study to illustrate how the theory guides problem framing before designing prescriptive artifacts.

Key Results

The theory establishes a rigorous criterion for unambiguous boundary semantics, context-dependent interaction traceability to successful stakeholder goal satisfaction, and sufficiency of problem-space specification over which disciplined reasoning can occur independent of solution design.

Limitations

The theory is demonstrated only through a hypothetical case study, lacking empirical validation in real-world systems engineering projects.

Resources

Paper