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Janos Kramar
Janos Kramar
DeepMind
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Cited by
Cited by
Year
Zoneout: Regularizing rnns by randomly preserving hidden activations
D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ...
arXiv preprint arXiv:1606.01305, 2016
3162016
Reinforcement and imitation learning for diverse visuomotor skills
Y Zhu, Z Wang, J Merel, A Rusu, T Erez, S Cabi, S Tunyasuvunakool, ...
arXiv preprint arXiv:1802.09564, 2018
2522018
OpenSpiel: A framework for reinforcement learning in games
M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint arXiv:1908.09453, 2019
1232019
Guidelines for artificial intelligence containment
J Babcock, J Kramár, RV Yampolskiy
Next-Generation Ethics: Engineering a Better Society (Ed.) Ali. E. Abbas, 90-112, 2019
482019
The AGI containment problem
J Babcock, J Kramár, R Yampolskiy
International Conference on Artificial General Intelligence, 53-63, 2016
422016
Learning reciprocity in complex sequential social dilemmas
T Eccles, E Hughes, J Kramár, S Wheelwright, JZ Leibo
arXiv preprint arXiv:1903.08082, 2019
292019
Learning to play no-press diplomacy with best response policy iteration
T Anthony, T Eccles, A Tacchetti, J Kramár, I Gemp, T Hudson, N Porcel, ...
Advances in Neural Information Processing Systems 33, 17987-18003, 2020
262020
OpenSpiel: a framework for reinforcement learning in games. CoRR abs/1908.09453 (2019)
M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint cs.LG/1908.09453, 2019
152019
Reinforcement and imitation learning for a task
S Tunyasuvunakool, Y Zhu, J Merel, J Kramar, Z Wang, NMO Heess
US Patent App. 16/174,112, 2019
82019
The Imitation Game: Learned Reciprocity in Markov games.
T Eccles, E Hughes, J Kramár, S Wheelwright, JZ Leibo
AAMAS, 1934-1936, 2019
82019
A generalized-zero-preserving method for compact encoding of concept lattices
M Skala, V Krakovna, J Kramár, G Penn
Proceedings of the 48th annual meeting of the Association for Computational …, 2010
62010
Should I tear down this wall? Optimizing social metrics by evaluating novel actions
J Kramár, N Rabinowitz, T Eccles, A Tacchetti
Coordination, Organizations, Institutions, Norms, and Ethics for Governance …, 2017
42017
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent
I Gemp, R Savani, M Lanctot, Y Bachrach, T Anthony, R Everett, ...
arXiv preprint arXiv:2106.01285, 2021
32021
How intelligible is intelligence?
A Salamon, S Rayhawk, J Kramár
Proceedings of the VIII European conference on computing and philosophy …, 2010
32010
A Neural Network Auction For Group Decision Making Over a Continuous Space.
Y Bachrach, IM Gemp, M Garnelo, J Kramar, T Eccles, D Rosenbaum, ...
IJCAI, 4976-4979, 2021
22021
Training a policy neural network for controlling an agent using best response policy iteration
TW Anthony, TE Eccles, A Tacchetti, J Kramár, IM Gemp, TC Hudson, ...
US Patent App. 17/570,870, 2022
2022
Neural Design of Contests and All-Pay Auctions using Multi-Agent Simulation
T Anthony, I Gemp, J Kramar, T Eccles, A Tacchetti, Y Bachrach
2019
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Articles 1–17