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Alexey Skrynnik
Alexey Skrynnik
AIRI
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Title
Cited by
Cited by
Year
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
362019
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
312021
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
28*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
28*2021
Hybrid policy learning for multi-agent pathfinding
A Skrynnik, A Yakovleva, V Davydov, K Yakovlev, AI Panov
IEEE Access 9, 126034-126047, 2021
182021
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
17*2023
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
142016
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
102022
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
82022
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
82022
Hierarchical reinforcement learning with clustering abstract machines
S Alexey, AI Panov
Artificial Intelligence: 17th Russian Conference, RCAI 2019, Ulyanovsk …, 2019
72019
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
62023
Pathfinding in stochastic environments: learning vs planning
A Skrynnik, A Andreychuk, K Yakovlev, A Panov
PeerJ Computer Science 8, e1056, 2022
62022
POGEMA: partially observable grid environment for multiple agents
A Skrynnik, A Andreychuk, K Yakovlev, AI Panov
arXiv preprint arXiv:2206.10944, 2022
62022
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
62020
Моделирование химической аварии на предприятии г. Рыбинска
НВ Сакова, АА Скрынник
Вестник Рыбинской государственной авиационной технологической академии им …, 2015
52015
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
42021
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
32023
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