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Navigating Assistance System for Quadcopter with Deep Reinforcement Learning
A deep reinforcement learning method for quadcopter to bypass obstacles in 3D environment. -
Selective Particle Attention: Visual Feature-Based Attention in Deep Reinforc...
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... -
Geometric Multi-Model Fitting
A geometric multi-model fitting dataset -
A3C-S: Automated Agent Accelerator Co-Search
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... -
MB2C: Model-Based Deep Reinforcement Learning for Multi-Zone Building Control
The dataset used in this paper is a building dataset for multi-zone building control, including the design of those key components. -
Deep Reinforcement Learning for Simultaneous Sensing and Channel Access in Co...
The dataset is used for dynamic spectrum access in cognitive wireless networks, where only partial observations are available to the users due to narrowband sensing and... -
Pong from Pixels
A deep reinforcement learning model for playing Atari Pong. -
End-to-End Motion Planning of Quadrotors Using Deep Reinforcement Learning
The proposed method uses raw depth images obtained from a front-facing camera and directly generates local motion plans in the form of smooth motion primitives that move a... -
User-Guided Personalized Image Aesthetic Assessment
Personalized image aesthetic assessment framework using deep reinforcement learning -
Autonomous Braking System via Deep Reinforcement Learning
The proposed autonomous braking system learns an intelligent way of brake control from the experiences obtained under the simulated environment. -
Sentence Simplification with Deep Reinforcement Learning
Sentence simplification with deep reinforcement learning. -
MultiExit-DRL
Multi-exit evacuation simulation dataset using Deep Reinforcement Learning (DRL) framework. -
Atari 2600 Environment
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... -
AirSim car simulator dataset
The dataset used in this paper is a human demonstration dataset for autonomous vehicles, consisting of images from a center camera. -
AACHER: Assorted Actor-Critic Deep Reinforcement Learning with Hindsight Expe...
Actor-Critic Deep Reinforcement Learning with Hindsight Experience Replay -
Hedging American Put Options with Deep Reinforcement Learning
The dataset used in this study for training and testing DRL agents to hedge American put options. -
Prioritized Sequence Experience Replay
Prioritized Sequence Experience Replay (PSER) is a novel framework for prioritizing sequences of transitions to both learn more efficiently and effectively. -
Learning to Recommend Frame for Interactive Video Object Segmentation in the ...
The paper proposes a framework for interactive video object segmentation (VOS) in the wild, where users can choose some frames for annotations iteratively. -
An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms
A Deep Reinforcement Learning framework for task arrangement in crowdsourcing platforms.
