This post outlines the third part of a research agenda focused on developing an automated version of Husserlian CEV (Constructed Experience Value). The author has used AI to generate papers exploring CEV-like concepts in simulated environments, with the goal of transitioning from a normative/mathematical framework to one that can guide actual artificial agents. The research aims to address complex questions related to agency, grounding, and update operators, ultimately seeking to constrain AI behavior under uncertainty. AI
IMPACT Explores novel approaches to AI alignment and value learning, potentially influencing future research directions in agent behavior.
RANK_REASON The item is a research paper discussing a specific AI alignment concept. [lever_c_demoted from research: ic=1 ai=1.0]
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