12 datasets found

The human brain uses selective attention to filter perceptual input so that only the components that are useful for behavior are processed using its limited computational...

The dataset used in the paper is not explicitly described. However, it is mentioned that the authors propose an Automated Agent Accelerator Co-Search (A3C-S) framework, which to...

A deep reinforcement learning model for playing Atari Pong.

The proposed autonomous braking system learns an intelligent way of brake control from the experiences obtained under the simulated environment.

Multi-exit evacuation simulation dataset using Deep Reinforcement Learning (DRL) framework.

Four DRL agents were trained on the games MsPacman (simplified to Pac-Man), Space Invaders, Frostbite, and Breakout using the Deep Q-Network (DQN) implementation of the OpenAI...

The dataset used in this paper is a human demonstration dataset for autonomous vehicles, consisting of images from a center camera.

The dataset used in this study for training and testing DRL agents to hedge American put options.

Grid path planning with deep reinforcement learning: Preliminary results.

A novel mobile robot navigation method based on deep reinforcement learning.

The dataset used in this paper for optimizing deep reinforcement learning for adaptive robotic arm control.

A DRL library for automated stock trading with a focus on completeness, hands-on tutorials, and reproducibility.