What is recorded here?
Learned a reward predictor from pairwise human judgments over trajectory segments and used it to train agents on Atari and simulated locomotion without direct access to the task reward.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The record is the 2017 six-author experimental paper. It does not establish general alignment, eliminate reward misspecification or cover later language-model RLHF pipelines.
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People and systems
Paul Christiano; Jan Leike; Tom B. Brown; Miljan Martic; Shane Legg; Dario Amodei
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.
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English catalogue narrative
Christiano and colleagues: deep reinforcement learning from human preferences
Learned a reward predictor from pairwise human judgments over trajectory segments and used it to train agents on Atari and simulated locomotion without direct access to the task reward.
Scientific scope
The record is the 2017 six-author experimental paper. It does not establish general alignment, eliminate reward misspecification or cover later language-model RLHF pipelines.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Paul Christiano; Jan Leike; Tom B. Brown; Miljan Martic; Shane Legg; Dario Amodei
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.