… The first uses deep neural … a deep reinforcement learning (DRL) agent to play the beer
game, a popular classroom activity that demonstrates certain aspects of inventory management. …

… Thus, when the target is a new product, it is difficult to optimize inventory control from its …
deep reinforcement learning with high sample efficiency and propose an inventory management …

… Because it is conventional in computer science literature to ‘maximize rewards’ instead of
‘minimizing costs’ in inventory management, we will define the reward as the negation of the …

… Deep Reinforcement Learning (DRL) is a general purpose technique for sequential decision
making that has yielded good results for various challenging inventory … warehouse inventory…

… To allow for a stringent performance analysis of the A3C algorithm in inventory management,
we develop two sets of experiments. The first experiment considers small-scale settings for …

This paper leverages recent developments in reinforcement learning and deep learning to
solve the supply chain inventory management (SCIM) problem, a complex sequential decision…

… As we have recently witnessed some applications of DRL in inventory management, we
believe the technique also bears substantial further promise for our field. The most apparent …

… paper proposes use of Deep Reinforcement Learning (RL) techniques for the inventory
management of perishable goods. The paper models the retailers inventory limitation factors and …

… Methodology: We propose a deep reinforcement learning (RL) algorithm to play the beer
game. Our algorithm makes no assumptions about costs or other settings. As with any …

… algorithm based on reinforcement learning and the inventory management methodology called
… For this, the inventory management problem is formulated as a Markov Decision Process …