Efficient water management in agriculture is essential for addressing the growing freshwater
scarcity crisis. Multi-Agent Reinforcement Learning (MARL) has emerged as a promising …

Non-stationarity is a fundamental challenge in multi-agent reinforcement learning (MARL),
where agents update their behaviour as they learn. Many theoretical advances in MARL …

Due to the high complexity of a football match, the opponents' strategies are variable and
unknown. Thus predicting the opponents' future intentions accurately based on current …

Non-stationarity poses a fundamental challenge in Multi-Agent Reinforcement Learning
(MARL), arising from agents simultaneously learning and altering their policies. This creates …

Intelligence and flexibility are the two main requirements for next-generation networks that
can be implemented in network slicing (NetS) technology. This intelligence and flexibility …

A highly competitive and confrontational football match is full of strategic and tactical
challenges. Therefore, player's cognition on their opponents' strategies and tactics is quite …

The deployment of machine learning systems in the market economy has triggered
academic and institutional fears over potential tacit collusion between fully automated …

Non-stationarity is a fundamental challenge in multi-agent reinforcement learning (MARL),
where agents update their behaviour as they learn. In multi-agent settings, individual agents …

The author wishes to express his profound gratitude and heartfelt appreciation to Jun Chen,
Ph. D., my esteemed advisor, for the invaluable mentorship, support, and insightful guidance …

Maximizing the energy production in wind farms requires mitigating wake effects, a
phenomenon by which wind turbines create sub-optimal wind conditions for the turbines …