Discretization and Representation of a Complex Environment for On-Policy Reinforcement Learning for Obstacle Avoidance for Simulated Autonomous Mobile Agents
Abstract:In recent years, the demand for digitalization, automation, and smart systems in the airline industry has accelerated. Furthermore, due to the ongoing global pandemic as of 2022, airlines are faced with the challenge of offering flexibility in both cargo and passenger capacity. Studies show that the use of smart products and autonomous agents are expected to play a key part in the digital transformation of the logistics industry. This paper aims to examine the current state-of-the-art in multi-agent systems an… Show more
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