Summary
In this chapter, we covered the current state of reinforcement learning algorithms and the challenges in the field of robotics. We also tried to take a look at each of the challenges in detail. We also learned about the practical challenges and its proposed solutions. Cracking the solution for end-to-end robotics will be the biggest milestone for the AI community. At present, there are challenges with continuous improvements in algorithms and data processing units; however, the day we see robots doing general human tasks is not far off. In case, you want to follow-up some of the researches done in robot reinforcement learning then you would like to start with the options below:
- "Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates" by Shixiang Gu et al. 2016 (https://arxiv.org/pdf/1610.00633.pdf)
- "Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search" by Yahya et al. 2016 (https://arxiv.org/pdf/1610.00673.pdf...
