Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Parametrically Retargetable Decision-Makers Tend To Seek Power
Authors: Alex Turner, Prasad Tadepalli
NeurIPS 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We develop a simple, broad criterion of functional retargetability (definition 3.5) which is a sufficient condition for power-seeking tendencies. Theorem 3.6 (Multiply retargetable functions have orbit-level tendencies). If f is (Θ, A n B)-retargetable, then f(B | θ) n most: Θ f(A | θ). Proof outline (full proof in Appendix B). |
| Researcher Affiliation | Academia | Alexander Matt Turner, Prasad Tadepalli Oregon State University {turneale@, tadepall@eecs.}oregonstate.edu |
| Pseudocode | No | The paper describes various decision-making procedures conceptually and formally, but it does not include any explicitly labeled 'Pseudocode' or 'Algorithm' blocks. |
| Open Source Code | No | The paper does not contain any statements about making source code available or provide links to a code repository. |
| Open Datasets | No | The paper analyzes decision-making in environments such as the 'Pac-Man video game' and 'Montezuma s Revenge (MR).' While these are well-known game environments, the paper does not provide concrete access information like specific links, DOIs, repository names, or formal citations with authors and year for a dataset used in their analysis. |
| Dataset Splits | No | The paper is theoretical in nature and does not conduct experiments involving dataset splits, thus no validation split information is provided. |
| Hardware Specification | No | The paper does not specify any hardware details or computing resources used for its analysis or any potential simulations. |
| Software Dependencies | No | The paper does not list specific software dependencies or their version numbers that would be required to replicate any aspects of the work. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameter values, training configurations, or other system-level settings. |