6 citations · 19 across the 8 of their papers we have counts for
5 papers · 1 filter
Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions
Alexey Skrynnik, Zoya Volovikova, Marc-Alexandre Côté +9
The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy. However, execution of instructions in real or simulated e…
NeurIPS 2021 Competition IGLU: Interactive Grounded Language Understanding in a Collaborative Environment
Julia Kiseleva, Ziming Li, Mohammad Aliannejadi +12
Human intelligence has the remarkable ability to adapt to new tasks and environments quickly. Starting from a very young age, humans acquire new skills and learn how to solve new t…
Landmark Policy Optimization for Object Navigation Task
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. Recent works have show…
Hierarchical Deep Q-Network from Imperfect Demonstrations in Minecraft
Alexey Skrynnik, Aleksey Staroverov, Ermek Aitygulov +3
We present Hierarchical Deep Q-Network (HDQfD) that took first place in the MineRL competition. HDQfD works on imperfect demonstrations and utilizes the hierarchical structure of e…
Automatic formation of the structure of abstract machines in hierarchical reinforcement learning with state clustering
Aleksandr I. Panov, Aleksey Skrynnik
We introduce a new approach to hierarchy formation and task decomposition in hierarchical reinforcement learning. Our method is based on the Hierarchy Of Abstract Machines (HAM) fr…