Summary of Four Original Theories: Foundational Trait Locking & Game Theory System (Core Theoretical System of Independent Researcher Relike Zhou) I. Foundational Theory Trait Locking Science DOI (Zenodo): 10.5281/zenodo.18337462; DOI (Figshare): 10.6084/m9.figshare.30940868.v1 Core Positioning: A foundational theory that breaks the "rational man hypothesis". It holds that decision-making is locked by inherent traits (such as cognitive models) with stable predictability, serving as the core support for the entire game theory system. Theoretical Source: Derived from the method framework of: Research on Rigid Constraint Method for Core Characteristics of Dynamic Systems and Its Applications DOI (Zenodo): 10.5281/zenodo.18336767 DOI (Figshare):10.6084/m9.figshare.30940475.v2 Core Tool: Technical Support for Complex System Prediction: Logic Chain-Driven Complex System Prediction: A New Paradigm Beyond Pure Mathematical Derivation DOI (Zenodo):10.5281/zenodo.18337817 DOI (Figshare):10.6084/m9.figshare.30968521.v1 II. Game Theory System (From Core to Application) Prediction-Regulation Dual-Drive Game Theory (Positive Game) DOI (Zenodo): 10.5281/zenodo.18339379; DOI (Figshare): 10.6084/m9.figshare.31061602.v1 Core Positioning: The core application framework based on Trait Locking Science. It constructs a "trait prediction → rule regulation → outcome guidance" model, emphasizing active game guidance rather than passive adaptation. Reverse Game Theory DOI (Zenodo): 10.5281/zenodo.18339072; DOI (Figshare): 10.6084/m9.figshare.31073821.v1 Core Positioning: An extension of Positive Game Theory for non-utilitarian scenarios. It proposes a "reverse trait locking → interaction reconstruction → consensus building" framework, supporting non-utilitarian human-machine cooperation. Theoretical Proof of Inevitable Human Victory in Human-Machine Frameworks DOI (Zenodo): 10.5281/zenodo.18339379 Core Positioning: A top-level practical achievement integrating the above three theories. It verifies the inevitability of human victory over AI through a "prediction-regulation-reverse transformation" loop, with the core mechanism of locking AI’s boundaries and converting its attacks.

Abstract:Aiming at the core pain point in the field of existing dynamic system control, which is "emphasizing parameter iterative optimization while neglecting rigid control of core traits", this paper formally proposes "Trait Locking Science (TLS)", a brand-new interdisciplinary subject. Taking "precise identification, rigid locking and full-link control of core traits in dynamic systems" as the research object, the core paradigm of this subject is "replacing iterative optimization with trait locking", which achieves the goal of stable system control without high computational power dependence and across wide scenes, and completely breaks through the computational power constraints and scene adaptation bottlenecks of traditional control schemes. This paper systematically constructs the theoretical system, technical framework and application branches of Trait Locking Science, and clarifies its boundary differences from related disciplines such as control engineering and recursive science. Based on the existing theoretical verification results and patented technology (Application No.: 2025118568506), the core advantages and engineering feasibility of the subject, including low computational power consumption, high stability and fast scene adaptation, are verified through multiple scenarios such as aerospace, industry and civil use. The establishment of Trait Locking Science fills the academic gap of "targeted control of core traits" in the field of dynamic system control, provides a subversive new paradigm for stable control in many fields such as aerospace, industrial manufacturing and intelligent equipment, and also builds a basic framework for subsequent academic research and industrial applications.

四大原创理论综述:基础特质锁定与博弈论体系 (独立研究者周子健 | Zhou, Relike 核心理论体系) 一、基础理论 特质锁定学 DOI (Zenodo): 10.5281/zenodo.18337462; DOI (Figshare): 10.6084/m9.figshare.30940868.v1 核心定位:突破“理性人假设”的基础理论,认为决策行为受内在特质(如认知模式等)锁定,具备稳定可预测性,是整个博弈论体系的核心支撑。 理论源头:源自以下研究的方法框架:《动态系统核心特质刚性约束方法及应用研究》 DOI (Zenodo): 10.5281/zenodo.18336767 DOI (Figshare):10.6084/m9.figshare.30940475.v2 核心工具:复杂系统预测的技术支撑:《逻辑链驱动的复杂系统预测:超越纯数学推导的新范式》 DOI (Zenodo):10.5281/zenodo.18337817 DOI (Figshare):10.6084/m9.figshare.30968521.v1 二、博弈论体系(从核心到应用) 预判-调控双驱博弈论(正向博弈) DOI (Zenodo): 10.5281/zenodo.18339379; DOI (Figshare): 10.6084/m9.figshare.31061602.v1 核心定位:基于特质锁定学的核心应用框架,构建“特质预判→规则调控→结果引导”模型,强调主动引导博弈走向,而非被动适应。 反向博弈论 DOI (Zenodo): 10.5281/zenodo.18339072; DOI (Figshare): 10.6084/m9.figshare.31073821.v1 核心定位:正向博弈论在非功利场景的延伸,提出“反向特质锁定→互动重构→共识达成”框架,为非功利性人机协作提供支撑。 人机框架内人类必胜的理论证明 DOI (Zenodo): 10.5281/zenodo.18339379 核心定位:整合上述三大理论的顶层实践成果,通过“预判-调控-反向转化”闭环验证人机博弈中人类必胜的必然性,核心机制为锁定人工智能边界、转化其攻击逻辑。

摘要:针对现有动态系统控制领域“重参数迭代优化、轻核心特质刚性管控”的核心痛点,本文正式提出“特质锁定学(Trait Locking Science, TLS)”这一全新交叉学科。该学科以“动态系统核心特质的精准识别、刚性锁定与全链路管控”为研究对象,核心范式是“以特质锁定替代迭代优化”,实现无需高算力依赖、跨场景广适配的系统稳定控制目标,彻底突破传统控制方案的算力束缚与场景适配瓶颈。本文系统构建了特质锁定学的理论体系、技术框架与应用分支,明确了其与控制工程、递归科学等相关学科的边界差异;并基于已有的理论验证成果与专利技术(申请号:2025118568506),从航天、工业、民用等多场景佐证了学科低算力消耗、高稳定性、快场景适配的核心优势与工程可落地性。特质锁定学的创立,填补了动态系统管控领域“核心特质靶向管控”的学术空白,为航天、工业制造、智能装备等多领域提供了颠覆性的稳定控制新范式,也为后续学术研究与产业应用搭建了基础框架。