Adaptive multi-agent stock trading decision support system based on deep reinforcement learning
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X Yuan, J Wang, S Gu, Y Guo, A Qi, S Li…
Engineering Applications of …, 2026
Elsevier
The stock market is a highly dynamic, complex, and uncertain environment, where traditional investment strategies and technical analysis tools often fail to provide reliable guidance, leading to increased investment risk and uncertainty. This study aims to develop an adaptive multi-agent stock trading decision support system that can effectively respond to volatile market conditions while balancing returns and risk management. We propose a deep reinforcement learning framework based on the Dueling Deep Q-Network (Dueling DQN) …
