Search Results for author: Aleksandr I. Panov

Found 19 papers, 9 papers with code

Object-Centric Learning with Slot Mixture Module

no code implementations8 Nov 2023 Daniil Kirilenko, Vitaliy Vorobyov, Alexey K. Kovalev, Aleksandr I. Panov

Object-centric architectures usually apply a differentiable module to the entire feature map to decompose it into sets of entity representations called slots.

Clustering Object +1

Gradual Optimization Learning for Conformational Energy Minimization

1 code implementation5 Nov 2023 Artem Tsypin, Leonid Ugadiarov, Kuzma Khrabrov, Manvel Avetisian, Alexander Telepov, Egor Rumiantsev, Alexey Skrynnik, Aleksandr I. Panov, Dmitry Vetrov, Elena Tutubalina, Artur Kadurin

Our results demonstrate that the neural network trained with GOLF performs on par with the oracle on a benchmark of diverse drug-like molecules using $50$x less additional data.

Drug Discovery

Graphical Object-Centric Actor-Critic

no code implementations26 Oct 2023 Leonid Ugadiarov, Aleksandr I. Panov

Our algorithm performs better in a visually complex 3D robotic environment and a 2D environment with compositional structure than the state-of-the-art model-free actor-critic algorithm built upon transformer architecture and the state-of-the-art monolithic model-based algorithm.

Object reinforcement-learning +1

Learning Successor Representations with Distributed Hebbian Temporal Memory

no code implementations20 Oct 2023 Evgenii Dzhivelikian, Petr Kuderov, Aleksandr I. Panov

This paper presents a novel approach to address the challenge of online hidden representation learning for decision-making under uncertainty in non-stationary, partially observable environments.

Decision Making Decision Making Under Uncertainty +1

Recurrent Memory Decision Transformer

no code implementations15 Jun 2023 Arkadii Bessonov, Alexey Staroverov, Huzhenyu Zhang, Alexey K. Kovalev, Dmitry Yudin, Aleksandr I. Panov

This paper proposes the Recurrent Memory Decision Transformer (RMDT), a model that uses a recurrent memory mechanism for reinforcement learning problems.

Atari Games reinforcement-learning

Intrinsic Motivation in Model-based Reinforcement Learning: A Brief Review

no code implementations24 Jan 2023 Artem Latyshev, Aleksandr I. Panov

The reinforcement learning research area contains a wide range of methods for solving the problems of intelligent agent control.

Model-based Reinforcement Learning reinforcement-learning +1

HPointLoc: Point-based Indoor Place Recognition using Synthetic RGB-D Images

1 code implementation30 Dec 2022 Dmitry Yudin, Yaroslav Solomentsev, Ruslan Musaev, Aleksei Staroverov, Aleksandr I. Panov

To study the main stages of solving the place recognition problem on the HPointLoc dataset, we proposed a new modular approach named as PNTR.

Image Retrieval Retrieval +2

POGEMA: Partially Observable Grid Environment for Multiple Agents

1 code implementation22 Jun 2022 Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev, Aleksandr I. Panov

We introduce POGEMA (https://github. com/AIRI-Institute/pogema) a sandbox for challenging partially observable multi-agent pathfinding (PO-MAPF) problems .

IGLU Gridworld: Simple and Fast Environment for Embodied Dialog Agents

1 code implementation31 May 2022 Artem Zholus, Alexey Skrynnik, Shrestha Mohanty, Zoya Volovikova, Julia Kiseleva, Artur Szlam, Marc-Alexandre Coté, Aleksandr I. Panov

We present the IGLU Gridworld: a reinforcement learning environment for building and evaluating language conditioned embodied agents in a scalable way.

reinforcement-learning Reinforcement Learning (RL)

Long-Term Exploration in Persistent MDPs

1 code implementation21 Sep 2021 Leonid Ugadiarov, Alexey Skrynnik, Aleksandr I. Panov

Exploration is an essential part of reinforcement learning, which restricts the quality of learned policy.

Reinforcement Learning (RL)

Landmark Policy Optimization for Object Navigation Task

no code implementations17 Sep 2021 Aleksey Staroverov, Aleksandr I. Panov

This work studies object goal navigation task, which involves navigating to the closest object related to the given semantic category in unseen environments.

Object

Delta Schema Network in Model-based Reinforcement Learning

1 code implementation17 Jun 2020 Andrey Gorodetskiy, Alexandra Shlychkova, Aleksandr I. Panov

This work is devoted to unresolved problems of Artificial General Intelligence - the inefficiency of transfer learning.

Model-based Reinforcement Learning reinforcement-learning +2

Psychologically inspired planning method for smart relocation task

no code implementations27 Jul 2016 Aleksandr I. Panov, Konstantin Yakovlev

On the subsymbolic level the task of path planning is considered and solved as a graph search problem.

Behavior and path planning for the coalition of cognitive robots in smart relocation tasks

no code implementations27 Jul 2016 Aleksandr I. Panov, Konstantin Yakovlev

In this paper we outline the approach of solving special type of navigation tasks for robotic systems, when a coalition of robots (agents) acts in the 2D environment, which can be modified by the actions, and share the same goal location.

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