activity
20232026
most citedPOGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfinding

5 citations · 7 across the 10 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

Decentralized Master-Mind: Joint Action Refinement through Iterative Intent Denoising in Multi-Agent Pathfinding

Valeriy Vyaltsev, Anton Andreychuk, Taisia Zlotnikova +3

Decentralized multi-agent path finding (MAPF) with communication requires agents to reach individual goals without collisions under partial observability. Learnable policies traine…

cs.AI2026

Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding

Valeriy Vyaltsev, Alsu Sagirova, Anton Andreychuk +5

Multi-agent pathfinding (MAPF) is a widely used abstraction for multi-robot trajectory planning problems, where multiple homogeneous agents move simultaneously within a shared envi…

cs.AI2026

MARL-GPT: Foundation Model for Multi-Agent Reinforcement Learning

Maria Nesterova, Mikhail Kolosov, Anton Andreychuk +6

Recent advances in multi-agent reinforcement learning (MARL) have demonstrated success in numerous challenging domains and environments, but typically require specialized models fo…

cs.AI2025

Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning

Anton Andreychuk, Konstantin Yakovlev, Aleksandr Panov +1

Multi-agent pathfinding (MAPF) is a common abstraction of multi-robot trajectory planning problems, where multiple homogeneous robots simultaneously move in the shared environment.…

cs.AI2024

Optimal and Bounded Suboptimal Any-Angle Multi-agent Pathfinding

Konstantin Yakovlev, Anton Andreychuk, Roni Stern

Multi-agent pathfinding (MAPF) is the problem of finding a set of conflict-free paths for a set of agents. Typically, the agents' moves are limited to a pre-defined graph of possib…

cs.AI2024

Improved Anonymous Multi-Agent Path Finding Algorithm

Zain Alabedeen Ali, Konstantin Yakovlev

We consider an Anonymous Multi-Agent Path-Finding (AMAPF) problem where the set of agents is confined to a graph, a set of goal vertices is given and each of these vertices has to…

cs.AI2023★ 1 cited

Decentralized Monte Carlo Tree Search for Partially Observable Multi-agent Pathfinding

Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev +1

The Multi-Agent Pathfinding (MAPF) problem involves finding a set of conflict-free paths for a group of agents confined to a graph. In typical MAPF scenarios, the graph and the age…