MIRI Technical Reports
webCredibility Rating
Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.
Rating inherited from publication venue: MIRI
MIRI's technical reports are foundational references for theoretical AI alignment research, particularly for those interested in agent foundations and decision theory; some papers like 'Logical Induction' are widely cited across the broader AI safety community.
Metadata
Summary
The Machine Intelligence Research Institute (MIRI) technical reports page hosts a collection of formal research papers and technical documents focused on the mathematical and theoretical foundations of AI alignment. These reports cover topics such as decision theory, logical uncertainty, agent foundations, and corrigibility. The collection represents MIRI's core research output aimed at solving fundamental problems in building safe and aligned AI systems.
Key Points
- •Houses MIRI's primary research output on agent foundations, decision theory, and mathematical AI alignment approaches
- •Includes seminal works on topics like Löbian obstacles, logical induction, and updateless decision theory
- •Represents a formal, mathematics-first approach to AI safety rather than empirical or engineering-focused methods
- •Many reports address foundational problems in building agents that behave safely under self-reference and uncertainty
- •Serves as a key reference for researchers working on theoretical AI alignment and agent design
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI Risk Interaction Network Model | Analysis | 64.0 |
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