1 code implementation • 14 Nov 2021 • Francisco Caio Lima Paiva, Leonardo Kanashiro Felizardo, Reinaldo Augusto da Costa Bianchi, Anna Helena Reali Costa
The feasibility of making profitable trades on a single asset on stock exchanges based on patterns identification has long attracted researchers.
no code implementations • 14 Dec 2020 • 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 heterogeneous agent graph, in which node labels denote agent classes and edge labels, the communication type between two classes of agents.
Multi-agent Reinforcement Learning Reinforcement Learning (RL)
no code implementations • 28 Sep 2020 • 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.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 28 Sep 2020 • Douglas De Rizzo Meneghetti, Thiago Pedro Donadon Homem, Jonas Henrique Renolfi de Oliveira, Isaac Jesus da Silva, Danilo Hernani Perico, Reinaldo Augusto da Costa Bianchi
We train multiple open implementations of MobileNetV2 and MobileNetV3 models with different underlying architectures, as well as YOLOv3, TinyYOLOv3, YOLOv4 and TinyYOLOv4 in an annotated image data set captured using a mobile robot.