7 citations · 7 across the 3 of their papers we have counts for
8 papers
rSoccer: A Framework for Studying Reinforcement Learning in Small and Very Small Size Robot Soccer
Felipe B. Martins, Mateus G. Machado, Hansenclever F. Bassani +2
Reinforcement learning is an active research area with a vast number of applications in robotics, and the RoboCup competition is an interesting environment for studying and evaluat…
An analysis of Reinforcement Learning applied to Coach task in IEEE Very Small Size Soccer
Carlos H. C. Pena, Mateus G. Machado, Mariana S. Barros +6
The IEEE Very Small Size Soccer (VSSS) is a robot soccer competition in which two teams of three small robots play against each other. Traditionally, a deterministic coach agent wi…
A Framework for Studying Reinforcement Learning and Sim-to-Real in Robot Soccer
Hansenclever F. Bassani, Renie A. Delgado, José Nilton de O. Lima Junior +5
This article introduces an open framework, called VSSS-RL, for studying Reinforcement Learning (RL) and sim-to-real in robot soccer, focusing on the IEEE Very Small Size Soccer (VS…
Deep Categorization with Semi-Supervised Self-Organizing Maps
Pedro H. M. Braga, Heitor R. Medeiros, Hansenclever F. Bassani
Nowadays, with the advance of technology, there is an increasing amount of unstructured data being generated every day. However, it is a painful job to label and organize it. Label…
Learning to Play Soccer by Reinforcement and Applying Sim-to-Real to Compete in the Real World
Hansenclever F. Bassani, Renie A. Delgado, Jose Nilton de O. Lima Junior +3
This work presents an application of Reinforcement Learning (RL) for the complete control of real soccer robots of the IEEE Very Small Size Soccer (VSSS), a traditional league in t…
MOEA/D with Uniformly Randomly Adaptive Weights
Lucas R. C. de Farias, Pedro H. M. Braga, Hansenclever F. Bassani +1
When working with decomposition-based algorithms, an appropriate set of weights might improve quality of the final solution. A set of uniformly distributed weights usually leads to…