In recent years, the swift progress of artificial intelligence (AI) has significantly influenced
trading practices, providing traders with advanced algorithms that improve decision-making …

Abstract Recent advancements in Large Language Models (LLMs) have exhibited notable
efficacy in question-answering (QA) tasks across diverse domains. Their prowess in …

Multi-task optimization problems in the real world often contain constraints. When dealing
with these problems, it is necessary to consider multiple tasks and their respective …

The economic system serves as the foundation for the organization and coordination of
economic activities within a society, involving various interacting agents, such as workers …

Recent advancements in Large Language Models (LLMs) have exhibited notable efficacy in
question-answering (QA) tasks across diverse domains. Their prowess in integrating …

The decisions traders make to buy or sell an asset depend on various analyses, with
expertise required to identify patterns that can be exploited for profit. In this paper we identify …

Reinforcement Learning (RL) is increasingly being applied to complex decision-making
tasks such as financial trading. However, designing effective reward functions remains a …

Finance provides a major contribution to countries economic growth. A deep understanding
of the financial market helps to offer better financial returns in the future. The financial market …

Synchronous reluctance motors offer several advantages that make them suitable for use in
electric vehicle traction systems. Motor-drive systems constitute the most significant share of …

In the world of automated stock trading, Deep Reinforcement Learning (DRL) techniques
have become highly effective due to their inherent capability of learning optimal trading …