A survey of progress on cooperative multi-agent reinforcement learning in open environment

L Yuan, Z Zhang, L Li, C Guan, Y Yu - ar** for efficient cooperative multi-agent reinforcement learning
Y Zang, J He, K Li, H Fu, Q Fu… - Advances in Neural …, 2023 - proceedings.neurips.cc
Grou** is ubiquitous in natural systems and is essential for promoting efficiency in team
coordination. This paper proposes a novel formulation of Group-oriented Multi-Agent …

Tesseract: Tensorised actors for multi-agent reinforcement learning

A Mahajan, M Samvelyan, L Mao… - International …, 2021 - proceedings.mlr.press
Reinforcement Learning in large action spaces is a challenging problem. This is especially
true for cooperative multi-agent reinforcement learning (MARL), which often requires …

Semantically aligned task decomposition in multi-agent reinforcement learning

W Li, D Qiao, B Wang, X Wang, B **, H Zha - arxiv preprint arxiv …, 2023 - arxiv.org
The difficulty of appropriately assigning credit is particularly heightened in cooperative
MARL with sparse reward, due to the concurrent time and structural scales involved …

Regularized softmax deep multi-agent q-learning

L Pan, T Rashid, B Peng, L Huang… - Advances in Neural …, 2021 - proceedings.neurips.cc
Tackling overestimation in $ Q $-learning is an important problem that has been extensively
studied in single-agent reinforcement learning, but has received comparatively little attention …

Combining behaviors with the successor features keyboard

WC Carvalho, A Saraiva, A Filos… - Advances in neural …, 2023 - proceedings.neurips.cc
Abstract The Option Keyboard (OK) was recently proposed as a method for transferring
behavioral knowledge across tasks. OK transfers knowledge by adaptively combining …