Bayesian Belief Updating in Neural Networks
An analysis of how deep learning architectures approximate Bayesian inference, including limitations in priors selection and posterior calibration.
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The Gettier Problem in Automated Knowledge Verification
Exploring how classic philosophical counterexamples to justified true belief manifest in AI-generated content and automated fact-checking pipelines.
Semantic Frames & Conceptual Blending Theory
Interactive knowledge graph mapping cognitive linguistics concepts to computational semantic networks and NLP vector space models.
Algorithmic Skepticism & Epistemic Vigilance
Formalizing computational approaches to detecting misinformation, including trust metrics, source provenance tracking, and adversarial robustness.
Embedded Cognition: From Situated AI to Extended Mind
How modern embodied AI systems challenge traditional internalist epistemology, proposing frameworks for distributed knowledge states.
Formal Epistemic Logic for Multi-Agent Systems
A survey of modal logics used to model knowledge, belief, and common knowledge in decentralized AI networks and blockchain consensus.