1 code implementation • 8 Jan 2021 • Mehran Taghian, Ahmad Asadi, Reza Safabakhsh
The proposed model consists of an encoder which is a neural structure responsible for learning informative features from the input sequence, and a decoder which is a DRL model responsible for learning profitable strategies based on the features extracted by the encoder.
1 code implementation • 27 Oct 2020 • Mehran Taghian, Ahmad Asadi, Reza Safabakhsh
The effect of different input representations on the performance of the models is investigated and the performance of DRL-based models in different markets and asset situations is studied.
no code implementations • 26 Jun 2019 • Ahmad Asadi, Reza Safabakhsh
The existing approaches are based on neural encoder-decoder structures equipped with the attention mechanism.