Zobrazeno 1 - 8
of 8
pro vyhledávání: '"János Kramár"'
Autor:
János Kramár, Tom Eccles, Ian Gemp, Andrea Tacchetti, Kevin R. McKee, Mateusz Malinowski, Thore Graepel, Yoram Bachrach
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-15 (2022)
Artificial Intelligence has achieved success in a variety of single-player or competitive two-player games with no communication between players. Here, the authors propose an approach where Artificial Intelligence agents have ability to negotiate and
Externí odkaz:
https://doaj.org/article/5f223cd84fe5408ebddd08eaf714cb79
Autor:
Tom Eccles, János Kramár, Dan Rosenbaum, Yoram Bachrach, Marta Garnelo, Ian Gemp, Thore Graepel
Publikováno v:
IJCAI
We propose a system for conducting an auction over locations in a continuous space. It enables participants to express their preferences over possible choices of location in the space, selecting the location that maximizes the total utility of all ag
Publikováno v:
Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XIII ISBN: 9783030723750
COIN(E)@AAMAS
COIN(E)@AAMAS
One of the fundamental challenges of governance is deciding when and how to intervene in multi-agent systems in order to impact group-wide metrics of success. This is particularly challenging when proposed interventions are novel and expensive. For e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f5c8ccd1a547ee16ba9e438ae76f6a8
https://doi.org/10.1007/978-3-030-72376-7_7
https://doi.org/10.1007/978-3-030-72376-7_7
With almost daily improvements in capabilities of artificial intelligence it is more important than ever to develop safety software for use by the AI research community. Building on our previous work on AI Containment Problem we propose a number of g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ba770e61876e29d6e6a852cb8e81c1b
https://doi.org/10.1017/9781108616188.008
https://doi.org/10.1017/9781108616188.008
Autor:
Ziyu Wang, Nando de Freitas, Saran Tunyasuvunakool, Raia Hadsell, Andrei Rusu, Serkan Cabi, Yuke Zhu, Josh Merel, Nicolas Heess, Tom Erez, János Kramár
Publikováno v:
Robotics: Science and Systems
We propose a model-free deep reinforcement learning method that leverages a small amount of demonstration data to assist a reinforcement learning agent. We apply this approach to robotic manipulation tasks and train end-to-end visuomotor policies tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e223b3355ed5af0a9400def814b8a551
http://arxiv.org/abs/1802.09564
http://arxiv.org/abs/1802.09564
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract We propose a multi-agent learning approach for designing crowdsourcing contests and All-Pay auctions. Prizes in contests incentivise contestants to expend effort on their entries, with different prize allocations resulting in different incen
Externí odkaz:
https://doaj.org/article/ac0fa5f3c87144e4ac64cde763a00528
Publikováno v:
Artificial General Intelligence ISBN: 9783319416489
AGI
AGI
There is considerable uncertainty about what properties, capabilities and motivations future AGIs will have. In some plausible scenarios, AGIs may pose security risks arising from accidents and defects. In order to mitigate these risks, prudent early
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::227a1112927efa96fffea91ddb717e9f
https://doi.org/10.1007/978-3-319-41649-6_6
https://doi.org/10.1007/978-3-319-41649-6_6
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319416489
There is considerable uncertainty about what properties, capabilities and motivations future AGIs will have. In some plausible scenarios, AGIs may pose security risks arising from accidents and defects. In order to mitigate these risks, prudent early
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e2875d3389ed6ee034dd387474acaa1
https://doi.org/10.1007/978-3-319-41649-6
https://doi.org/10.1007/978-3-319-41649-6