剖析通用人工智能中嵌入式智能体的失效机制
Formalizing Embeddedness Failures in Universal Artificial Intelligence
- 从通用人工智能框架出发，形式化嵌入式智能体的失败模式
- 证明特定变体AIXI在联合行动/感知历史下必然出现失效
- 为构建可靠嵌入式智能理论提供关键诊断依据
我们严谨探讨了普遍认为的通用强化学习智能体AIXI在建模嵌入式智能时所表现出的缺陷。本文尝试形式化这些失效模式，并证明其在通用人工智能框架内确实存在，重点关注一种将联合动作/感知历史视为来自通用分布的AIXI变体。同时，我们评估了基于AIXI变体建立成功嵌入式智能理论所取得的进展。
原文摘要 · Abstract (English)
We rigorously discuss the commonly asserted failures of the AIXI reinforcement learning agent as a model of embedded agency. We attempt to formalize these failure modes and prove that they occur within the framework of universal artificial intelligence, focusing on a variant of AIXI that models the joint action/percept history as drawn from the universal distribution. We also evaluate the progress that has been made towards a successful theory of embedded agency based on variants of the AIXI agent.
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