WorldSeed: The Grounding of Semantic Reality – Solving Hallucination and Deception via Axiomatic Constraints

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Authors: Xiaolong Zhang
Cited by: 0

Abstract

The Physics of Truth: Extending WorldSeed from Robotics to Semantics Why is it impossible for a robot to lift a 10-ton rock, yet trivial for an AI (or human) to claim "I can lift a 10-ton rock"? This paper identifies the root cause of both AI Hallucination and Human Deception: the lack of "Energy Cost" in the textual domain (W_Text). In a frictionless semantic environment, generating a lie is thermodynamically equivalent to generating the truth. This work extends the WorldSeed SABO Protocol (State, Action, Boundary, Observer) from the domain of physical robotics (Sim2Real) to the domain of semantic truth (Sim2Fact). We propose that Truth is not a statistical property of language, but a computable property of Grounded State (S) and Costly Action (A). Key Contributions: The Theory of Semantic Gravity: Introducing axiomatic constraints (On-chain State, Action Staking) to make deception computationally or economically prohibitive. SABO Audit of Lies: Analyzing the structural flaws of decoupled observation (O ≠ S) in LLMs and social contracts. Three Case Studies:• Literary Hallucination: Using logic boundaries to reject impossible narratives (e.g., Lin Daiyu uprooting a willow tree).• Financial Fraud: Replacing CEO claims with Zero-Knowledge Proofs of Solvency.• Social Default: Using smart contract staking to enforce promises. The Theorem of Semantic Convergence: A formal proof demonstrating that under a strict WorldSeed Runtime, divergent linguistic descriptions must collapse into a unique ontological fixed point. "Meaning is Execution." This paper completes the WorldSeed trinity by providing the philosophical and sociological framework that complements the Axiomatic Specification and the Civilization Operating System.

Fields of Study & Subjects

Ethics and Social Impacts of AI Computability Logic AI Algorithms Innovation Sustainability Human-Machine Systems

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
5 January 2026
Document type
Thesis