mlsanityData to 14 Oct 2026

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode

arXiv 2403.00318 ↗First posted 1 Mar 2024cs.AI cs.LGcited by 0

On the map: Deep reinforcement learning methods → RL for energy, networks and operations

Abstract (arXiv)

We introduce a deep reinforcement learning (DRL) approach for solving management problems including inventory management, dynamic pricing, and recommendation. This DRL approach has the potential to lead to a large management model based on certain transformer neural network structures, resulting in an artificial general intelligence paradigm for various management tasks. Traditional methods have limitations for solving complex real-world problems, and we demonstrate how DRL can surpass existing heuristic approaches for solving management tasks. We aim to solve the problems in a unified framework, considering the interconnections between different tasks. Central to our methodology is the development of a foundational decision model coordinating decisions across the different domains through generative decision-making. Our experimental results affirm the effectiveness of our DRL-based framework in complex and dynamic business environments. This work opens new pathways for the application of DRL in management problems, highlighting its potential to revolutionize traditional business management.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL for energy, networks and operations, one of 15 directions in Deep reinforcement learning methods. Builds on 5 of its 27 references that are in the map. First posted on arXiv 1 Mar 2024.

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5 of 27 references.

References · 5

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
  3. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,258
  4. 2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,546
  5. 2021Offline Reinforcement Learning as One Big Sequence Modeling Problemcited by 644

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