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Found 4 papers, 2 papers with code
Towards General Computer Control: A Multimodal Agent for Red Dead Redemption II as a Case Study
Despite the success in specific tasks and scenarios, existing foundation agents, empowered by large models (LMs) and advanced tools, still cannot generalize to different scenarios, mainly due to dramatic differences in the observations and actions across scenarios.
A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist
Notably, FinAgent is the first advanced multimodal foundation agent designed for financial trading tasks.
EarnHFT: Efficient Hierarchical Reinforcement Learning for High Frequency Trading
In stage II, we construct a pool of diverse RL agents for different market trends, distinguished by return rates, where hundreds of RL agents are trained with different preferences of return rates and only a tiny fraction of them will be selected into the pool based on their profitability.
Market-GAN: Adding Control to Financial Market Data Generation with Semantic Context
Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making.
