Abstract Knowledge graph embedding (KGE) projects entities and relations into low-
dimension continuous vector space, which promotes the widespread use of knowledge …

Featured Application SC-M* generalizes the M* algorithm to address real-world multi-agent
path planning problems in the soft-collision context, which considers the allocation of …

Generating dynamic node representation via limited samples at a time is a challenging task.
Meanwhile, the human brain can quickly capture dynamic features without much information …

We present a congestion-aware routing solution for indoor evacuation, which produces real-
time individual-customized evacuation routes among multiple destinations while keeping …

Abstract Knowledge Graph (KG) is the network which contains some topic-based entities,
called nodes, and the associated information among the entities. Here, the concept in the …

Sequential multiagent decision-making under partial observability and uncertainty poses
several challenges. Although multiagent reinforcement learning (MARL) approaches have …

In this paper, we study the cooperative path planning and motion coordination problems of
the multi-robot system with large number of robots, aiming for practical applications in …

Abstract Knowledge graphs (KGs) are regarded as important resources for a variety of
artificial intelligence (AI) and auxiliary decision tasks but suffer from incompleteness. To …

This paper proposes a paradigm for coordination of multiple unmanned aerial vehicle (UAV)
clusters in a shared motion space. UAVs are arranged in a finite number of teams each …

While Knowledge Graphs (KGs) have long been used as valuable sources of structured
knowledge, in recent years, KG embeddings have become a popular way of deriving …