4 answers
3
Asked 765 views

How to do Reinforced Learning

#computer-programming #datascience

computer-programming datascience
Answer This

+25 Karma if successful
From: You
To: Friend
Subject: Career question for you
3

4 answers

1
Updated
Share a link to this answer
Share a link to this answer

Dhairya’s Answer

This is a bit of vague question. It would be helpful to understand the context of the problems you're interested in solving. It would also be helpful to get a sense of your math and coding background.

If you curious about the space in general and looking to get started, checkout OpenAI's Spinning up in Deep RL tutorials. They start from the foundations and work up to implementing standard policy optimization algorithms for solving RL problems in the Open AI gyms (agents playing various various video games). Note they do assume general knowledge of calculus, linear algebra and basic python coding.

https://spinningup.openai.com/en/latest/spinningup/rl_intro.html
1
0
Updated
Share a link to this answer
Share a link to this answer

Riste’s Answer

Hey Huangyuan, Artificial Intelligence and Machine Learning are very fascinating technologies. I have provided some next steps so you get a better understanding of the technologies and have some real world product examples from the platform leaders in the market. Feel free to reach out to me if you have any questions or need more pointers. Best of luck and success.

Riste recommends the following next steps:

Watch the Machine Learning & Artificial Intelligence: Crash Course - https://www.youtube.com/watch?v=z-EtmaFJieY
Review the products offered by Microsoft - https://azure.microsoft.com/en-us/overview/ai-platform/
Review the products offered by Google - https://cloud.google.com/products/ai
Review the products offered by Amazon https://aws.amazon.com/machine-learning/
Check out the top blogs e.g. https://www.reddit.com/r/MachineLearning/
0
0
Updated
Share a link to this answer
Share a link to this answer

karthik’s Answer

Investigating circumstances
Deciding an action by applying some tactics
Performing the action
Obtaining a reward
Discovering new areas with the help of past experiences and improving the approach
Iteratively sticking to the strategy and performing the action until the machine learns properly
0
0
Updated
Share a link to this answer
Share a link to this answer

karthik’s Answer

Reinforcement learning is the training of machine learning models to make a sequence of decisions. The agent learns to achieve a goal in an uncertain, potentially complex environment. In reinforcement learning, an artificial intelligence faces a game-like situation. The computer employs trial and error to come up with a solution to the problem. To get the machine to do what the programmer wants, the artificial intelligence gets either rewards or penalties for the actions it performs. Its goal is to maximize the total reward.
Although the designer sets the reward policy–that is, the rules of the game–he gives the model no hints or suggestions for how to solve the game. It’s up to the model to figure out how to perform the task to maximize the reward, starting from totally random trials and finishing with sophisticated tactics and superhuman skills. By leveraging the power of search and many trials, reinforcement learning is currently the most effective way to hint machine’s creativity. In contrast to human beings, artificial intelligence can gather experience from thousands of parallel gameplays if a reinforcement learning algorithm is run on a sufficiently powerful computer infrastructure
0