most citedIntelligent Trading Systems: A Sentiment-Aware Reinforcement Learning Approach

12 citations · 24 across the 4 of their papers we have counts for

collaborators

4 papers

q-fin.TR2021★ 12 cited

Intelligent Trading Systems: A Sentiment-Aware Reinforcement Learning Approach

Francisco Caio Lima Paiva, Leonardo Kanashiro Felizardo, Reinaldo Augusto da Costa Bianchi +1

The feasibility of making profitable trades on a single asset on stock exchanges based on patterns identification has long attracted researchers. Reinforcement Learning (RL) and Na…

cs.AI2020★ 1 cited

Specializing Inter-Agent Communication in Heterogeneous Multi-Agent Reinforcement Learning using Agent Class Information

Douglas De Rizzo Meneghetti, Reinaldo Augusto da Costa Bianchi

Inspired by recent advances in agent communication with graph neural networks, this work proposes the representation of multi-agent communication capabilities as a directed labeled…

cs.AI2020★ 10 cited

Towards Heterogeneous Multi-Agent Reinforcement Learning with Graph Neural Networks

Douglas De Rizzo Meneghetti, Reinaldo Augusto da Costa Bianchi

This work proposes a neural network architecture that learns policies for multiple agent classes in a heterogeneous multi-agent reinforcement setting. The proposed network uses dir…

cs.CV2020★ 1 cited

Detecting soccer balls with reduced neural networks: a comparison of multiple architectures under constrained hardware scenarios

Douglas De Rizzo Meneghetti, Thiago Pedro Donadon Homem, Jonas Henrique Renolfi de Oliveira +3

Object detection techniques that achieve state-of-the-art detection accuracy employ convolutional neural networks, implemented to have optimal performance in graphics processing un…