14 citations · 52 across the 24 of their papers we have counts for
27 papers
Relational Object-Centric Actor-Critic
Leonid Ugadiarov, Vitaliy Vorobyov, Aleksandr I. Panov
The advances in unsupervised object-centric representation learning have significantly improved its application to downstream tasks. Recent works highlight that disentangled object…
Learning Successor Features with Distributed Hebbian Temporal Memory
Evgenii Dzhivelikian, Petr Kuderov, Aleksandr I. Panov
This paper presents a novel approach to address the challenge of online sequence learning for decision making under uncertainty in non-stationary, partially observable environments…
Evaluation of Safety Constraints in Autonomous Navigation with Deep Reinforcement Learning
Brian Angulo, Gregory Gorbov, Aleksandr Panov +1
While reinforcement learning algorithms have had great success in the field of autonomous navigation, they cannot be straightforwardly applied to the real autonomous systems withou…
Monte-Carlo Tree Search for Multi-Agent Pathfinding: Preliminary Results
Yelisey Pitanov, Alexey Skrynnik, Anton Andreychuk +2
In this work we study a well-known and challenging problem of Multi-agent Pathfinding, when a set of agents is confined to a graph, each agent is assigned a unique start and goal v…
Recurrent Action Transformer with Memory
Egor Cherepanov, Alexey Staroverov, Alexey K. Kovalev +1
Transformers have become increasingly popular in offline reinforcement learning (RL) due to their ability to treat agent trajectories as sequences, reframing policy learning as a s…
Intrinsic Motivation in Model-based Reinforcement Learning: A Brief Review
Artem Latyshev, Aleksandr I. Panov
The reinforcement learning research area contains a wide range of methods for solving the problems of intelligent agent control. Despite the progress that has been made, the task o…