| Deep reinforcement learning from human preferences PF Christiano, J Leike, T Brown, M Martic, S Legg, D Amodei Advances in Neural Information Processing Systems, 4299-4307, 2017 | 361 | 2017 |
| AI Safety Gridworlds J Leike, M Martic, V Krakovna, PA Ortega, T Everitt, A Lefrancq, L Orseau, ... arXiv preprint arXiv:1711.09883, 2017 | 155 | 2017 |
| Learning to Understand Goal Specifications by Modelling Reward D Bahdanau, F Hill, J Leike, E Hughes, P Kohli, E Grefenstette arXiv preprint arXiv:1806.01946, 2018 | 62* | 2018 |
| Reward learning from human preferences and demonstrations in Atari B Ibarz, J Leike, T Pohlen, G Irving, S Legg, D Amodei Advances in Neural Information Processing Systems, 8011-8023, 2018 | 56 | 2018 |
| Ranking Templates for Linear Loops J Leike, M Heizmann Logical Methods in Computer Science, 2015 | 56 | 2015 |
| Linear ranking for linear lasso programs M Heizmann, J Hoenicke, J Leike, A Podelski Automated Technology for Verification and Analysis, 365-380, 2013 | 49 | 2013 |
| Scalable agent alignment via reward modeling: a research direction J Leike, D Krueger, T Everitt, M Martic, V Maini, S Legg arXiv preprint arXiv:1811.07871, 2018 | 47 | 2018 |
| Ultimate Automizer with array interpolation M Heizmann, D Dietsch, J Leike, B Musa, A Podelski International Conference on Tools and Algorithms for the Construction and …, 2015 | 28 | 2015 |
| Ultimate automizer with two-track proofs M Heizmann, D Dietsch, M Greitschus, J Leike, B Musa, C Schätzle, ... International Conference on Tools and Algorithms for the Construction and …, 2016 | 27 | 2016 |
| Thompson sampling is asymptotically optimal in general environments J Leike, T Lattimore, L Orseau, M Hutter Conference on Uncertainty in Artificial Intelligence, 2016 | 26 | 2016 |
| Bad universal priors and notions of optimality J Leike, M Hutter Conference on Learning Theory, 1244-1259, 2015 | 25 | 2015 |
| Geometric nontermination arguments J Leike, M Heizmann International Conference on Tools and Algorithms for the Construction and …, 2018 | 21* | 2018 |
| Universal Reinforcement Learning Algorithms: Survey and Experiments J Aslanides, J Leike, M Hutter arXiv preprint arXiv:1705.10557, 2017 | 16 | 2017 |
| Nonparametric general reinforcement learning J Leike PhD thesis, Australian National University, 2016 | 14 | 2016 |
| On the computability of Solomonoff induction and knowledge-seeking J Leike, M Hutter International Conference on Algorithmic Learning Theory, 364-378, 2015 | 13 | 2015 |
| A formal solution to the grain of truth problem J Leike, J Taylor, B Fallenstein Conference on Uncertainty in Artificial Intelligence, 2016 | 10 | 2016 |
| Active reinforcement learning: Observing rewards at a cost D Krueger, J Leike, O Evans, J Salvatier Future of Interactive Learning Machines, NIPS Workshop, 2016 | 10* | 2016 |
| Sequential extensions of causal and evidential decision theory T Everitt, J Leike, M Hutter International Conference on Algorithmic DecisionTheory, 205-221, 2015 | 10 | 2015 |
| Synthesis for polynomial lasso programs J Leike, A Tiwari International Conference on Verification, Model Checking, and Abstract …, 2014 | 7 | 2014 |
| Learning Human Objectives by Evaluating Hypothetical Behavior S Reddy, AD Dragan, S Levine, S Legg, J Leike arXiv preprint arXiv:1912.05652, 2019 | 6 | 2019 |
Marcus HutterResearcher@DeepMind & Professor at ANUVerified email at anu.edu.au
