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Found 3 papers, 1 papers with code
Fairness in Multi-agent Reinforcement Learning for Stock Trading
In this paper, we propose a novel scheme that utilizes multi-agent reinforcement learning systems to derive stock trading strategies for all clients which keep a balance between revenue and fairness.
Spatial Influence-aware Reinforcement Learning for Intelligent Transportation System
We demonstrate three types of directed communications to show the effect of directions of social influence on the entire network utility and individual utility.
Multi-Agent Deep Reinforcement Learning for Liquidation Strategy Analysis
Liquidation is the process of selling a large number of shares of one stock sequentially within a given time frame, taking into consideration the costs arising from market impact and a trader's risk aversion.
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