The paper introduces ‘Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games’. It discusses how classical multi-agent reinforcement learning (MARL) assumes risk neutrality and complete objectivity for agents, which falls…
Continue readingThis research paper explores the fusion of computational experiments and Large Language Models (LLMs) in studying complex systems. Computational experiments are valuable for studying complex systems, but accurately representing real…
Continue readingThis academic paper discusses the potential of autonomous cyber defense in industrial control systems, with a focus on maritime operational technology (OT). It introduces a simulation environment, IPMSRL, for a…
Continue readingThe study presents a method for dynamically configuring Model Predictive Controllers (MPC) to resolve local navigation issues based on the information represented in the semantic graph world model. The MPC…
Continue readingThe article presents a novel approach to collaborative vehicle routing (CVR), a process where carriers share transportation requests to achieve economies of scale. This method reduces costs, greenhouse gas emissions,…
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