2 citations · 3 across the 2 of their papers we have counts for
4 papers
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…
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…
CAPTION: Correction by Analyses, POS-Tagging and Interpretation of Objects using only Nouns
Leonardo Anjoletto Ferreira, Douglas De Rizzo Meneghetti, Paulo Eduardo Santos
Recently, Deep Learning (DL) methods have shown an excellent performance in image captioning and visual question answering. However, despite their performance, DL methods do not le…
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…