用加权权威构建可验证的科学认知网络，提升机器对真理的推理能力。
Bayesian Epistemology with Weighted Authority: A Formal Architecture for Truth-Promoting Autonomous Scientific Reasoning
- 将科学主张建模为带作者和时效性的概率信念
- 通过复制评分与引用加权动态更新可信度
- 适合需要可信推理与审计的科研自动化系统
科学文献的指数级增长已超出人类专家和现有AI系统的认知处理能力。本文提出贝叶斯认知框架加权权威（BEWA），将信念形式化为结构化科学主张上的动态概率函数。每个主张均带上下文、作者归属，并通过复制得分、引用权重和时间衰减进行评估。信念更新采用证据条件下的贝叶斯推断、矛盾处理及认知衰减机制。该架构支持基于图的主张传播、作者信誉建模、密码锚定及零知识审计验证。通过将科学推理转化为可计算验证的认知网络，BEWA推动了促进真理效用、理性信念收敛与审计鲁棒完整性的机器推理系统发展。
原文摘要 · Abstract (English)
The exponential expansion of scientific literature has surpassed the epistemic processing capabilities of both human experts and current artificial intelligence systems. This paper introduces Bayesian Epistemology with Weighted Authority (BEWA), a formally structured architecture that operationalises belief as a dynamic, probabilistically coherent function over structured scientific claims. Each claim is contextualised, author-attributed, and evaluated through a system of replication scores, citation weighting, and temporal decay. Belief updates are performed via evidence-conditioned Bayesian inference, contradiction processing, and epistemic decay mechanisms. The architecture supports graph-based claim propagation, authorial credibility modelling, cryptographic anchoring, and zero-knowledge audit verification. By formalising scientific reasoning into a computationally verifiable epistemic network, BEWA advances the foundation for machine reasoning systems that promote truth utility, rational belief convergence, and audit-resilient integrity across dynamic scientific domains.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。