The last decade witnessed a great development of automated driving vehicles (ADVs) and
vehicle intelligence. The significant increment of machine intelligence poses a new …

Abstract Multi-Target Tracking Guidance (MTTG) in unknown environments has great
potential values in applications for Unmanned Aerial Vehicle (UAV) swarms. Although Multi …

The current work utilized a multi-agent reinforcement learning (MARL) algorithm embedded
in a continuous predator-prey pursuit simulation environment to measure and evaluate …

Artificial intelligence (AI) has enormous potential for military applications. Fully realizing the
conceived benefits of AI requires effective interactions among Soldiers and computational …

In multi-agent systems, agents' abilities are often used to classify a system as either
homogeneous or heterogeneous. In the context of multi-agent reinforcement learning …

When considering collaboration among agents in multi-agent systems, individual and team
measures of performance are used to describe the collaboration. Typically, the definition of …

Although we have previously observed the emergence of collaboration, or more specifically,
coordination between cooperative agents in a Predator-Prey Pursuit task, we have yet to …

抄録 In multi-agent environments, reinforcement learning (RL) has shown strong potential
especially with the recent developments. However, there exist different difficulties in …

Like human organizations, agent teams are often formed to take advantage of 7
supplementary similarities or complementary differences [7]. Similarity is leveraged 8 by …