Search Results for author: Artem Zholus

Found 15 papers, 7 papers with code

Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation

no code implementations9 Dec 2024 Egor Cherepanov, Nikita Kachaev, Artem Zholus, Alexey K. Kovalev, Aleksandr I. Panov

Using these definitions, we categorize different classes of agent memory, propose a robust experimental methodology for evaluating the memory capabilities of RL agents, and standardize evaluations.

Reinforcement Learning (RL)

Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent

no code implementations16 Jul 2024 Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, Mohammad Reza Samsami, Artem Zholus, Sonia Joseph, Blake Richards, Irina Rish, Özgür Şimşek

Understanding the mechanisms behind decisions taken by large foundation models in sequential decision making tasks is critical to ensuring that such systems operate transparently and safely.

Decision Making Minecraft +1

BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning

no code implementations6 Jun 2024 Artem Zholus, Maksim Kuznetsov, Roman Schutski, Rim Shayakhmetov, Daniil Polykovskiy, Sarath Chandar, Alex Zhavoronkov

Generating novel active molecules for a given protein is an extremely challenging task for generative models that requires an understanding of the complex physical interactions between the molecule and its environment.

Graph Reconstruction Language Modeling +1

Mastering Memory Tasks with World Models

1 code implementation7 Mar 2024 Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar

Through a diverse set of illustrative tasks, we systematically demonstrate that R2I not only establishes a new state-of-the-art for challenging memory and credit assignment RL tasks, such as BSuite and POPGym, but also showcases superhuman performance in the complex memory domain of Memory Maze.

Model-based Reinforcement Learning State Space Models

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 +1

Multitask Adaptation by Retrospective Exploration with Learned World Models

no code implementations25 Oct 2021 Artem Zholus, Aleksandr I. Panov

Model-based reinforcement learning (MBRL) allows solving complex tasks in a sample-efficient manner.

Model-based Reinforcement Learning

Continuous Histogram Loss: Beyond Neural Similarity

no code implementations6 Apr 2020 Artem Zholus, Evgeny Putin

Similarity learning has gained a lot of attention from researches in recent years and tons of successful approaches have been recently proposed.

Data Visualization Representation Learning

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