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Andreychuk, Anton
34  Ergebnisse:
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1

When to Switch: Planning and Learning for Partially Observa..:

Skrynnik, Alexey ; Andreychuk, Anton ; Yakovlev, Konstantin.
IEEE Transactions on Neural Networks and Learning Systems.  , 2024
Link: https://doi.org/10.1109/..
 
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2

Monte-Carlo Tree Search for Multi-agent Pathfinding: Prelim..:

, In: Lecture Notes in Computer Science; Hybrid Artificial Intelligent Systems,
Pitanov, Yelisey ; Skrynnik, Alexey ; Andreychuk, Anton.. - p. 649-660 , 2023
Link: https://doi.org/10.1007/..
 
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3

Analysis of the Anytime MAPF Solvers Based on the Combinati..:

, In: Advances in Computational Intelligence; Lecture Notes in Computer Science,
Ivanashev, Ilya ; Andreychuk, Anton ; Yakovlev, Konstantin - p. 368-382 , 2022
Link: https://doi.org/10.1007/..
 
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4

Pathfinding in stochastic environments: learning vs plannin:

Skrynnik, Alexey ; Andreychuk, Anton ; Yakovlev, Konstantin.
PeerJ Computer Science.  8 (2022)  - p. e1056 , 2022
Link: https://doi.org/10.7717/..
 
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5

Multi-agent pathfinding with continuous time:

Andreychuk, Anton ; Yakovlev, Konstantin ; Surynek, Pavel..
Artificial Intelligence.  305 (2022)  - p. 103662 , 2022
Link: https://doi.org/10.1016/..
 
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6

Multi-agent Path Finding with Kinematic Constraints via Con..:

, In: Artificial Intelligence; Lecture Notes in Computer Science,
Andreychuk, Anton - p. 29-45 , 2020
Link: https://doi.org/10.1007/..
 
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7

Prioritized Multi-agent Path Finding for Differential Drive..:

, In: 2019 European Conference on Mobile Robots (ECMR),
Yakovlev, Konstantin ; Andreychuk, Anton ; Vorobyev, Vitaly - p. 1-6 , 2019
Link: https://doi.org/10.1109/..
 
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8

Combining Safe Interval Path Planning and Constrained Path ..:

, In: Lecture Notes in Computer Science; Interactive Collaborative Robotics,
Yakovlev, Konstantin ; Andreychuk, Anton ; Belinskaya, Julia. - p. 310-319 , 2019
Link: https://doi.org/10.1007/..
 
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9

Two Techniques That Enhance the Performance of Multi-robot ..:

, In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems,
Andreychuk, Anton ; Yakovlev, Konstantin - p. 2177-2179 , 2018
Link: https://dl.acm.org/doi/1..
 
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10

Path Finding for the Coalition of Co-operative Agents Actin..:

, In: Lecture Notes in Computer Science; Interactive Collaborative Robotics,
Andreychuk, Anton ; Yakovlev, Konstantin - p. 13-22 , 2018
Link: https://doi.org/10.1007/..
 
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11

Learn to Follow: Decentralized Lifelong Multi-agent Pathfin..:

Skrynnik, Alexey ; Andreychuk, Anton ; Nesterova, Maria..
http://arxiv.org/abs/2310.01207.  , 2023
Link: http://arxiv.org/abs/231..
 
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12

Monte-Carlo Tree Search for Multi-Agent Pathfinding: Prelim..:

Pitanov, Yelisey ; Skrynnik, Alexey ; Andreychuk, Anton..
http://arxiv.org/abs/2307.13453.  , 2023
Link: http://arxiv.org/abs/230..
 
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13

Decentralized Monte Carlo Tree Search for Partially Observa..:

Skrynnik, Alexey ; Andreychuk, Anton ; Yakovlev, Konstantin.
http://arxiv.org/abs/2312.15908.  , 2023
Link: http://arxiv.org/abs/231..
 
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14

Analysis Of The Anytime MAPF Solvers Based On The Combinati..:

Ivanashev, Ilya ; Andreychuk, Anton ; Yakovlev, Konstantin
http://arxiv.org/abs/2209.09612.  , 2022
Link: http://arxiv.org/abs/220..
 
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15

POGEMA: Partially Observable Grid Environment for Multiple ..:

Skrynnik, Alexey ; Andreychuk, Anton ; Yakovlev, Konstantin.
http://arxiv.org/abs/2206.10944.  , 2022
Link: http://arxiv.org/abs/220..
 
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