Information for Tom Everitt

Table of contents

Basic information

Item Value
Facebook username tom.everitt
Intelligent Agent Foundations Forum username 108
Source [1]
Agendas Recursive reward modeling

List of positions (2 positions)

Organization Title Start date End date AI safety relation Subject Employment type Source Notes
Google DeepMind [2]
Australian National University [2], [3], [4], [5]

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Organization documents (0 documents)

Title Publication date Author Publisher Affected organizations Affected people Document scope Cause area Notes

Documents (1 document)

Title Publication date Author Publisher Affected organizations Affected people Affected agendas Notes
Scalable agent alignment via reward modeling: a research direction 2018-11-19 Jan Leike, David Krueger, Tom Everitt, Miljan Martic, Vishal Maini, Shane Legg arXiv Google DeepMind Recursive reward modeling, Imitation learning, inverse reinforcement learning, Cooperative inverse reinforcement learning, myopic reinforcement learning, iterated amplification, debate This paper introduces the (recursive) reward modeling agenda, discussing its basic outline, challenges, and ways to overcome those challenges. The paper also discusses alternative agendas and their relation to reward modeling.

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