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Found 6 papers, 0 papers with code
AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection
In this paper, we introduce the phenomenon of the Leaky Surface Wave (LSW), a novel sensing modality, and present AuraSense, a proximity detection system using the LSW.
Towards Practical Credit Assignment for Deep Reinforcement Learning
Credit assignment is a fundamental problem in reinforcement learning, the problem of measuring an action's influence on future rewards.
QXplore: Q-Learning Exploration by Maximizing Temporal Difference Error
We implement the objective with an adversarial Q-learning method in which Q and Qx are the action-value functions for extrinsic and secondary rewards, respectively.
Reward Prediction Error as an Exploration Objective in Deep RL
We then propose a deep reinforcement learning method, QXplore, which exploits the temporal difference error of a Q-function to solve hard exploration tasks in high-dimensional MDPs.
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies
CGP aims to combine the stability and performance of iterative sampling policies with the low computational cost of a policy network.
Program Synthesis Through Reinforcement Learning Guided Tree Search
Program Synthesis is the task of generating a program from a provided specification.
