| Self-modification of policy and utility function in rational agents T Everitt, D Filan, M Daswani, M Hutter International Conference on Artificial General Intelligence, 1-11, 2016 | 24 | 2016 |
| Feature reinforcement learning: state of the art M Daswani, P Sunehag, M Hutter Sequential decision-making with big data: papers from the AAAI-14 workshop, 2014 | 13 | 2014 |
| Q-learning for history-based reinforcement learning M Daswani, P Sunehag, M Hutter Asian Conference on Machine Learning, 213-228, 2013 | 8 | 2013 |
| A definition of happiness for reinforcement learning agents M Daswani, J Leike International Conference on Artificial General Intelligence, 231-240, 2015 | 7 | 2015 |
| Reinforcement learning with value advice M Daswani, P Sunehag, M Hutter Asian Conference on Machine Learning, 299-314, 2015 | 6 | 2015 |
| Feature Reinforcement Learning using Looping Suffix Trees M Daswani, P Sunehag, M Hutter JMLR Workshop and Conference Proceedings : EWRL 2012 24, 11-24, 2012 | 6 | 2012 |
| Network partition handling in fault-tolerant key management system J Leiseboer, M Daswani, T Bradbury, F Poppa, K Chong, J Green, ... US Patent 10,671,643, 2020 | 4 | 2020 |
| Fault-tolerant key management system J Leiseboer, M Daswani, T Bradbury, F Poppa, K Chong, J Green, ... US Patent 10,606,864, 2020 | 1 | 2020 |
| Fault-tolerant key management system J Leiseboer, M Daswani, T Bradbury, F Poppa, K Chong, J Green, ... US Patent App. 16/783,969, 2020 | | 2020 |
| Generic Reinforcement Learning Beyond Small MDPs M Daswani The Australian National University, 2015 | | 2015 |
Marcus HutterResearcher@DeepMind & Professor at ANUVerified email at anu.edu.au
