Deep Reinforcement Learning: A Brief Survey
Arizona State University · Institution of Engineering and Technology · +1 more institution
Abstract
Deep reinforcement learning (DRL) is poised to revolutionize the field of artificial intelligence (AI) and represents a step toward building autonomous systems with a higher-level understanding of the visual world. Currently, deep learning is enabling reinforcement learning (RL) to scale to problems that were previously intractable, such as learning to play video games directly from pixels. DRL algorithms are also applied to robotics, allowing control policies for robots to be learned directly from camera inputs in the real world. In this survey, we begin with an introduction to the general field of RL, then progress to the main streams of value-based and policy-based methods. Our survey will cover central…
Citation impact
- FWCI
- 140.68
- Percentile
- 100%
- References
- 252
Authors
4Topics & keywords
- Reinforcement learning
- Computer science
- Artificial intelligence
- Deep learning
- Field (mathematics)
- Artificial neural network
- Robotics
- Asynchronous communication