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Mega-reward: Achieving human-level play without extrinsic rewards

Abstract:

Intrinsic rewards were introduced to simulate how human intelligence works; they are usually evaluated by intrinsically-motivated play, i.e., playing games without extrinsic rewards but evaluated with extrinsic rewards. However, none of the existing intrinsic reward approaches can achieve human-level performance under this very challenging setting of intrinsically-motivated play. In this work, we propose a novel megalomania-driven intrinsic reward (called mega-reward), which, to our knowledge...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1609/aaai.v34i04.6040

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-7644-1668
Publisher:
Association for the Advancement of Artificial Intelligence
Journal:
34th AAAI Conference on Artificial Intelligence (AAAI 2020) More from this journal
Volume:
34
Issue:
4
Pages:
5826-5833
Publication date:
2020-06-16
Acceptance date:
2019-11-11
Event title:
34th AAAI Conference on Artificial Intelligence (AAAI 2020)
Event location:
New York, New York, USA
Event website:
https://aaai.org/Conferences/AAAI-20/
Event start date:
2020-02-07
Event end date:
2020-02-12
DOI:
EISSN:
2374-3468
ISSN:
2159-5399
ISBN:
9781577358091
Language:
English
Keywords:
Pubs id:
pubs:1082444
UUID:
uuid:0c49a2fd-6019-431d-bfe5-345d088da4ad
Local pid:
pubs:1082444
Source identifiers:
1082444
Deposit date:
2020-01-14

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