Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …

Despite the success of cooperative multi-agent reinforcement learning algorithms, most of
them focus on a single team composition, which prevents them from being used in more …

The advanced performance of the monocular depth estimation model highly relies on
features extracted by encoder networks. The encoder architecture in most previous methods …

Despite the success of cooperative multi-agent reinforcement learning algorithms, most of
them focus on a single team composition, which prevents them from being used in more …

Despite the success of Multi-Agent Reinforcement Learning (MARL) algorithms in
cooperative tasks, previous works, unfortunately, face challenges in heterogeneous …

Conventional neural architecture search (NAS) algorithms typically work on search spaces
with short-distance node connections. We argue that such designs, though safe and stable …