Large language models (LLMs) have exploded a new heatwave of AI for their ability to
engage end-users in human-level conversations with detailed and articulate answers across …

The large-scale integration of intermittent renewable energy resources introduces increased
uncertainty and volatility to the supply side of power systems, thereby complicating system …

Automated industries lead to high quality production, lower manufacturing cost and better
utilization of human resources. Robotic manipulator arms have major role in the automation …

Due to a lack of safety considerations, a wide range of multiagent reinforcement learning
(MARL) applications are limited in real-world environments. Thus, ensuring MARL safety is …

Ensuring the safety of Reinforcement Learning (RL) is crucial for its deployment in real-world
applications. Nevertheless, managing the trade-off between reward and safety during …

Large Language Models (LLMs) have demonstrated remarkable capabilities for
reinforcement learning (RL) models, such as planning and reasoning capabilities. However …

Reinforcement Learning (RL) has demonstrated remarkable success across various
domains. Nonetheless, a significant challenge in RL is to ensure safety, particularly when …

Ensuring safety in MARL, particularly when deploying it in real-world applications such as
autonomous driving, emerges as a critical challenge. To address this challenge, traditional …

Incorporating safety is an essential prerequisite for broadening the practical applications of
reinforcement learning in real-world scenarios. To tackle this challenge, Constrained Markov …

In numerous reinforcement learning (RL) problems involving safety-critical systems, a key
challenge lies in balancing multiple objectives while simultaneously meeting all stringent …