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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. -
Generalization in Deep Reinforcement Learning for Robotic Navigation by Rewar...
A novel reward function for reinforcement learning and a Soft Actor-Critic algorithm to train a DRL policy in the context of local navigation for autonomous mobile robots in... -
SCIMAI-Gym
The SCIM environment proposed in this paper is a stochastic and divergent two-echelon supply chain that includes a factory that can produce various product types, a factory... -
Grid path planning with deep reinforcement learning: Preliminary results
Grid path planning with deep reinforcement learning: Preliminary results. -
A novel mobile robot navigation method based on deep reinforcement learning
A novel mobile robot navigation method based on deep reinforcement learning. -
Optimizing Deep Reinforcement Learning for Adaptive Robotic Arm Control
The dataset used in this paper for optimizing deep reinforcement learning for adaptive robotic arm control.
