| Learning Markov State Abstractions for Deep Reinforcement Learning C Allen, N Parikh, O Gottesman, G Konidaris Advances in Neural Information Processing Systems 34, 2021 | 71 | 2021 |
| Mean Actor Critic C Allen, K Asadi, M Roderick, A Mohamed, G Konidaris, M Littman arXiv preprint arXiv:1709.00503, 2017 | 41* | 2017 |
| Evidence of Learned Look-Ahead in a Chess-Playing Neural Network E Jenner, S Kapur, V Georgiev, C Allen, S Emmons, SJ Russell Advances in Neural Information Processing Systems 37, 31410-31437, 2024 | 21 | 2024 |
| Optimistic Initialization for Exploration in Continuous Control S Lobel, O Gottesman, C Allen, A Bagaria, G Konidaris Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7612-7619, 2022 | 21 | 2022 |
| Efficient Black-Box Planning Using Macro-Actions with Focused Effects C Allen, M Katz, T Klinger, G Konidaris, M Riemer, G Tesauro Proceedings of the 30th International Joint Conference on Artificial …, 2021 | 13 | 2021 |
| Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy C Allen, AT Kirtland, RY Tao, S Lobel, D Scott, N Petrocelli, O Gottesman, ... Advances in Neural Information Processing Systems 37, 2024 | 7 | 2024 |
| Coarse-grained smoothness for rl in metric spaces O Gottesman, K Asadi, C Allen, S Lobel, G Konidaris, M Littman arXiv preprint arXiv:2110.12276, 2021 | 6* | 2021 |
| Bad-Policy Density: A Measure of Reinforcement Learning Hardness D Abel, C Allen, D Arumugam, DE Hershkowitz, ML Littman, LLS Wong ICML Workshop on Reinforcement Learning Theory, 2021 | 5 | 2021 |
| Benchmarking Partial Observability in Reinforcement Learning with a Suite of Memory-Improvable Domains RY Tao, K Guo, C Allen, G Konidaris Reinforcement Learning Conference, 2025 | 3 | 2025 |
| Task Scoping: Generating Task-Specific Simplifications of Open-Scope Planning Problems M Fishman, N Kumar, C Allen, N Danas, M Littman, S Tellex, G Konidaris IJCAI Workshop on Bridging the Gap Between AI Planning and Reinforcement …, 2023 | 3* | 2023 |
| Characterizing the Action-Generalization Gap in Deep Q-Learning Z Zhou, C Allen, K Asadi, G Konidaris Multidisciplinary Conference on Reinforcement Learning and Decision Making …, 2022 | 2 | 2022 |
| From Pixels to Factors: Learning Independently Controllable State Variables for Reinforcement Learning R Rodriguez-Sanchez, C Allen, G Konidaris arXiv preprint arXiv:2510.02484, 2025 | 1 | 2025 |
| Focused Skill Discovery: Learning to Control Specific State Variables while Minimizing Side Effects JC Carr, Q Sun, C Allen Reinforcement Learning Conference, 2025 | 1 | 2025 |
| General Value Discrepancies Mitigate Partial Observability in Reinforcement Learning P Koepernik, RY Tao, R Parr, G Konidaris, C Allen Finding the Frame Workshop at RLC, 2025 | 1 | 2025 |
| Memory as state abstraction over trajectories A Kirtland, A Ivanov, C Allen, M Littman, G Konidaris | 1 | 2025 |
| Improving Reward Learning by Estimating Annotator Expertise P Czempin, R Freedman, E Novoseller, VJ Lawhern, C Allen, E Bıyık RSS Workshop on Continual Robot Learning from Humans, 2025 | | 2025 |
| Learning Transferable Sub-Goals by Hypothesizing Generalizing Features ADM Koch, A Bagaria, B Huo, Z Zhou, C Allen, G Konidaris AAAI Workshop on Generalization in Planning, 2025 | | 2025 |
| Neural Manifold Geometry Encodes Feature Fields J Yocum, C Allen, B Olshausen, S Russell NeurIPS 2025 Workshop on Symmetry and Geometry in Neural Representations, 2025 | | 2025 |
| The Influence of Scaffolds on Coordination Scaling Laws in LLM Agents M Meireles, R Bhati, N Lauffer, C Allen Workshop on Scaling Environments for Agents, 2025 | | 2025 |
| Skill-Driven Neurosymbolic State Abstractions A Ahmetoglu, S James, C Allen, S Lobel, D Abel, G Konidaris Advances in Neural Information Processing Systems 38, 2025 | | 2025 |
George KonidarisBrownVerified email at cs.brown.edu
