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Mountain Car
The dataset used in the paper is a reinforcement learning dataset, specifically a Markov Decision Process (MDP) with a finite set of states and actions. -
Lunar Lander
The dataset used in this paper is a collection of data points from a lunar lander, which is used to test the proposed APG algorithm for task switching. -
Real-World Street Networks
The dataset used in the paper is a collection of real-world street networks. -
Irregular Graphs
The dataset used in the paper is a collection of 100-node irregular graphs. -
Generalized Value Iteration Networks
The dataset used in the paper is a collection of 2D mazes, irregular graphs, and real-world street networks. -
Mountain Car, Acrobot, and Gridworld
The dataset used in the paper is a reinforcement learning dataset, specifically the Mountain Car and Acrobot problems, and a Gridworld problem. -
Scaling robot learning with semantically imagined experience
Scaling robot learning with semantically imagined experience. -
Soft Actor-Critic Algorithm with Truly-satisfied Inequality Constraint
Soft actor-critic algorithm with truly-satisfied inequality constraint -
On-Ramp Merge Dataset
The dataset used in the paper is a simulated on-ramp merge scenario, with 3 vehicles involved. The dataset is used to train a Deep Reinforcement Learning model to learn an... -
DDPG from Demonstrations
The dataset used in the paper is a set of demonstrations for a robot insertion task, which is a continuous control problem. The demonstrations are collected by a robot... -
Autonomous UAV Navigation Using Reinforcement Learning
Autonomous UAV Navigation Using Reinforcement Learning -
Cooperative and Distributed Reinforcement Learning of Drones for Field Coverage
Cooperative and Distributed Reinforcement Learning of Drones for Field Coverage -
AACHER: Assorted Actor-Critic Deep Reinforcement Learning with Hindsight Expe...
Actor-Critic Deep Reinforcement Learning with Hindsight Experience Replay -
Tree-based reinforcement learning for optimal water reservoir operation
The authors propose a tree-based reinforcement learning approach for optimal water reservoir operation. -
Foreign Exchange Trading: A Risk-Averse Batch Reinforcement Learning Approach
The authors propose a risk-averse batch reinforcement learning approach for foreign exchange trading. -
Lifelong Hyper-Policy Optimization with Multiple Importance Sampling
The authors propose a lifelong RL approach that learns a hyper-policy, whose input is time, that outputs the parameters of the policy to be queried at that time. -
RL Boosting via Weak Supervised Learning
The dataset used in the paper is a reinforcement learning dataset, where the goal is to learn a policy that maximizes the expected return in a Markov decision process. -
Dual Policy Distillation
The dataset used in the paper is a continuous control task dataset. -
Cellular-Connected UAV Path Design
The dataset used in this paper for cellular-connected UAV path design with reinforcement learning. -
Reinforcement Learning-based Control of Nonlinear Systems using Carleman Appr...
We develop data-driven reinforcement learning (RL) control designs for input-affine nonlinear systems. We use Carleman linearization to express the state-space representation of...
