1.6k citations · 1.7k across the 17 of their papers we have counts for
8 papers · 1 filter
Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control with Action Constraints
Kazumi Kasaura, Shuwa Miura, Tadashi Kozuno +3
This study presents a benchmark for evaluating action-constrained reinforcement learning (RL) algorithms. In action-constrained RL, each action taken by the learning system must co…
ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives
Toshinori Kitamura, Ryo Yonetani
We present ShinRL, an open-source library specialized for the evaluation of reinforcement learning (RL) algorithms from both theoretical and practical perspectives. Existing RL lib…
Path Planning using Neural A* Search
Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain +2
We present Neural A*, a novel data-driven search method for path planning problems. Despite the recent increasing attention to data-driven path planning, machine learning approache…
Adaptive Distillation for Decentralized Learning from Heterogeneous Clients
Jiaxin Ma, Ryo Yonetani, Zahid Iqbal
This paper addresses the problem of decentralized learning to achieve a high-performance global model by asking a group of clients to share local models pre-trained with their own…
MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics
Mohammadamin Barekatain, Ryo Yonetani, Masashi Hamaya
Transfer reinforcement learning (RL) aims at improving the learning efficiency of an agent by exploiting knowledge from other source agents trained on relevant tasks. However, it r…
Decentralized Learning of Generative Adversarial Networks from Non-iid Data
Ryo Yonetani, Tomohiro Takahashi, Atsushi Hashimoto +1
This work addresses a new problem that learns generative adversarial networks (GANs) from multiple data collections that are each i) owned separately by different clients and ii) d…
Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data
Naoya Yoshida, Takayuki Nishio, Masahiro Morikura +2
This paper proposes a cooperative mechanism for mitigating the performance degradation due to non-independent-and-identically-distributed (non-IID) data in collaborative machine le…
MGpi: A Computational Model of Multiagent Group Perception and Interaction
Navyata Sanghvi, Ryo Yonetani, Kris Kitani
Toward enabling next-generation robots capable of socially intelligent interaction with humans, we present a of interactions in a social environmen…