1 citations · 2 across the 4 of their papers we have counts for
4 papers
MA-Dreamer: Coordination and communication through shared imagination
Kenzo Lobos-Tsunekawa, Akshay Srinivasan, Michael Spranger
Multi-agent RL is rendered difficult due to the non-stationary nature of environment perceived by individual agents. Theoretically sound methods using the REINFORCE estimator are i…
Point Cloud Based Reinforcement Learning for Sim-to-Real and Partial Observability in Visual Navigation
Kenzo Lobos-Tsunekawa, Tatsuya Harada
Reinforcement Learning (RL), among other learning-based methods, represents powerful tools to solve complex robotic tasks (e.g., actuation, manipulation, navigation, etc.), with th…
Using Convolutional Neural Networks in Robots with Limited Computational Resources: Detecting NAO Robots while Playing Soccer
Nicolás Cruz, Kenzo Lobos-Tsunekawa, Javier Ruiz-del-Solar
The main goal of this paper is to analyze the general problem of using Convolutional Neural Networks (CNNs) in robots with limited computational capabilities, and to propose genera…
Toward Real-Time Decentralized Reinforcement Learning using Finite Support Basis Functions
Kenzo Lobos-Tsunekawa, David L. Leottau, Javier Ruiz-del-Solar
This paper addresses the design and implementation of complex Reinforcement Learning (RL) behaviors where multi-dimensional action spaces are involved, as well as the need to execu…