| Object detection with deep neural networks for reinforcement learning in the task of autonomous vehicles path planning at the intersection DA Yudin, A Skrynnik, A Krishtopik, I Belkin, AI Panov Optical Memory and Neural Networks 28, 283-295, 2019 | 41 | 2019 |
| Hierarchical deep q-network from imperfect demonstrations in minecraft A Skrynnik, A Staroverov, E Aitygulov, K Aksenov, V Davydov, AI Panov Cognitive Systems Research 65, 74-78, 2021 | 32 | 2021 |
| Interactive grounded language understanding in a collaborative environment: Iglu 2021 J Kiseleva, Z Li, M Aliannejadi, S Mohanty, M ter Hoeve, M Burtsev, ... NeurIPS 2021 Competitions and Demonstrations Track, 146-161, 2022 | 31* | 2022 |
| Forgetful experience replay in hierarchical reinforcement learning from expert demonstrations A Skrynnik, A Staroverov, E Aitygulov, K Aksenov, V Davydov, AI Panov Knowledge-Based Systems 218, 106844, 2021 | 30* | 2021 |
| Interactive Grounded Language Understanding in a Collaborative Environment: Retrospective on Iglu 2022 Competition J Kiseleva, A Skrynnik, A Zholus, S Mohanty, N Arabzadeh, MA Côté, ... NeurIPS 2022 Competition Track, 204-216, 2023 | 18* | 2023 |
| Hybrid policy learning for multi-agent pathfinding A Skrynnik, A Yakovleva, V Davydov, K Yakovlev, AI Panov IEEE Access 9, 126034-126047, 2021 | 18 | 2021 |
| Personal cognitive assistant: concept and key principals IV Smirnov, AI Panov, AA Skrynnik, EV Chistova Informatika i Ee Primeneniya [Informatics and its Applications] 13 (3), 105-113, 2019 | 14* | 2019 |
| Hierarchical temporal memory implementation with explicit states extraction A Skrynnik, A Petrov, AI Panov Biologically Inspired Cognitive Architectures (BICA) for Young Scientists …, 2016 | 14 | 2016 |
| Iglu gridworld: Simple and fast environment for embodied dialog agents A Zholus, A Skrynnik, S Mohanty, Z Volovikova, J Kiseleva, A Szlam, ... arXiv preprint arXiv:2206.00142, 2022 | 11 | 2022 |
| Collecting interactive multi-modal datasets for grounded language understanding S Mohanty, N Arabzadeh, M Teruel, Y Sun, A Zholus, A Skrynnik, ... arXiv preprint arXiv:2211.06552, 2022 | 9 | 2022 |
| Learning to solve voxel building embodied tasks from pixels and natural language instructions A Skrynnik, Z Volovikova, MA Côté, A Voronov, A Zholus, N Arabzadeh, ... arXiv preprint arXiv:2211.00688, 2022 | 8 | 2022 |
| Pathfinding in stochastic environments: learning vs planning A Skrynnik, A Andreychuk, K Yakovlev, A Panov PeerJ Computer Science 8, e1056, 2022 | 7 | 2022 |
| Navigating autonomous vehicle at the road intersection simulator with reinforcement learning M Martinson, A Skrynnik, AI Panov Artificial Intelligence: 18th Russian Conference, RCAI 2020, Moscow, Russia …, 2020 | 7 | 2020 |
| Hierarchical reinforcement learning with clustering abstract machines S Alexey, AI Panov Artificial Intelligence: 17th Russian Conference, RCAI 2019, Ulyanovsk …, 2019 | 7 | 2019 |
| Automatic formation of the structure of abstract machines in hierarchical reinforcement learning with state clustering AI Panov, A Skrynnik arXiv preprint arXiv:1806.05292, 2018 | 7* | 2018 |
| Planning and learning in multi-agent path finding KS Yakovlev, AA Andreychuk, AA Skrynnik, AI Panov Doklady Mathematics 106 (Suppl 1), S79-S84, 2023 | 6 | 2023 |
| POGEMA: partially observable grid environment for multiple agents A Skrynnik, A Andreychuk, K Yakovlev, AI Panov arXiv preprint arXiv:2206.10944, 2022 | 6 | 2022 |
| When to switch: planning and learning for partially observable multi-agent pathfinding A Skrynnik, A Andreychuk, K Yakovlev, AI Panov IEEE Transactions on Neural Networks and Learning Systems, 2023 | 5 | 2023 |
| Моделирование химической аварии на предприятии г. Рыбинска НВ Сакова, АА Скрынник Вестник Рыбинской государственной авиационной технологической академии им …, 2015 | 5 | 2015 |
| Q-Mixing network for multi-agent pathfinding in partially observable grid environments V Davydov, A Skrynnik, K Yakovlev, A Panov Artificial Intelligence: 19th Russian Conference, RCAI 2021, Taganrog …, 2021 | 4 | 2021 |
Aleksandr I. PanovFRC CSC RAS, AIRI, MIPT在 airi.net 的电子邮件经过验证
