نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشکده کامپیوتر، دانشگاه یزد، یزد، ایران
2 هیأت علمی، دانشکده مهندسی کامپیوتر، دانشگاه یزد
3 دانشکده مهندسی کامپیوتر ، دانشگاه یزد، یزد، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Crypto currency market is a complex, uncertain and dynamic environment with significant volatility. Developing a trading strategy in this market is highly challenging and a key area of academic research. In this article, An autonomous trading agent has been designed to analyze the effects of traders' behavior (transactions they do) on changing market conditions. Although many factors influence the market, these effects impact ultimately through traders behaviors. In this article, The agent makes decisions only by reviewing and analyzing the transactions which has been done by traders. The agent is built using DDQN reinforcement learning algorithm. To train the agent, all HitBTC`s transactions during nearly 3 months for 3 cryptocurrency pairs have been gathered. The results show that the model converges and is stable. As a result, The transactions data are important source for decision making. Combining this method with price prediction methods can be a new approach in designing trader agents.
کلیدواژهها [English]
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