| On Q-learning Convergence for Non-Markov Decision Processes. SJ Majeed, M Hutter IJCAI 18, 2546-2552, 2018 | 50 | 2018 |
| Exact reduction of huge action spaces in general reinforcement learning SJ Majeed, M Hutter Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 8874-8883, 2021 | 10 | 2021 |
| Performance guarantees for homomorphisms beyond Markov decision processes SJ Majeed, M Hutter Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7659-7666, 2019 | 8 | 2019 |
| Abstractions of general reinforcement learning SJ Majeed arXiv preprint arXiv:2112.13404, 2021 | 7 | 2021 |
| Topological importance as an incentive to cooperate in mobile ad hoc networks: A game theoretic analysis SJ Majeed, H Mahmood 2012 14th International Conference on Advanced Communication Technology …, 2012 | 5 | 2012 |
| Abstractions of General Reinforcement Learning: An Inquiry into the Scalability of Generally Intelligent Agents SJ Majeed PQDT-Global, 2021 | 1 | 2021 |
| Conditions on features for temporal difference-like methods to converge M Hutter, S Yang-Zhao, SJ Majeed arXiv preprint arXiv:1905.11702, 2019 | 1 | 2019 |
| Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions SJ Majeed, M Hutter arXiv preprint arXiv:2112.13386, 2021 | | 2021 |
| Topological Incentives to Mitigate Selfishness in Wireless Ad Hoc Networks: A Game Theoretic Analysis SJ Majeed Quaid-i-Azam University, Islamabad Pakistan, 2012 | | 2012 |
Marcus HutterResearcher@DeepMind & Professor at ANUПотвърден имейл адрес: anu.edu.au
