Found 1358 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles

Reinforcement learning (RL) methods have been shown to be capable of learning intelligent behavior in rich domains. Expand abstract.
50 days ago
10/10 relevant
arXiv

Robust Domain Randomization for Reinforcement Learning

Producing agents that can generalize to a wide range of environments is a significant challenge in reinforcement learning. Expand abstract.
50 days ago
10/10 relevant
arXiv

Robust Model Predictive Shielding for Safe Reinforcement Learning with Stochastic Dynamics

Our goal is to ensure the safety of a control policy trained using reinforcement learning, e.g., in a simulated environment. Expand abstract.
50 days ago
10/10 relevant
arXiv

Reciprocal Collision Avoidance for General Nonlinear Agents using Reinforcement Learning

To reduce online computation, we first decompose the multi-agent scenario and solve a two agents collision avoidance problem using reinforcement learning (RL). Expand abstract.
50 days ago
10/10 relevant
arXiv

Learning Humanoid Robot Running Skills through Proximal Policy Optimization

In this work, we present a methodology based on Deep Reinforcement Learning that learns running skills without any prior knowledge, using a neural network whose inputs are related to robot's dynamics. Expand abstract.
51 days ago
4/10 relevant
arXiv

Resource Allocation in Mobility-Aware Federated Learning Networks: A Deep Reinforcement Learning Approach

However, federated learning faces the energy constraints of the workers and the high network resource cost due to the fact that a number of global model transmissions may be required to achieve the target accuracy. Expand abstract.
52 days ago
8/10 relevant
arXiv

Deep Reinforcement Learning Control of Quantum Cartpoles

We use the state-of-the-art deep reinforcement learning to stabilize the quantum cartpole and find that our deep learning approach performs comparably to or better than other strategies in standard control theory. Expand abstract.
52 days ago
10/10 relevant
arXiv

Dealing with Sparse Rewards in Reinforcement Learning

This project introduces a novel reinforcement learning solution by combining aspects of two existing state of the art sparse reward solutions, curiosity driven exploration and unsupervised auxiliary tasks. Expand abstract.
52 days ago
10/10 relevant
arXiv

Momentum in Reinforcement Learning

We adapt the optimization's concept of momentum to reinforcement learning. Expand abstract.
52 days ago
9/10 relevant
arXiv

Towards a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control

A novel approach is to use reinforcement learning (RL) to have an agent learn electric drive control from scratch merely by interacting with a suitable control environment. Expand abstract.
52 days ago
7/10 relevant
arXiv