EDGE OSDEFINITION
Q-learning is a model-free reinforcement learning algorithm that helps an AI agent learn how to make decisions. The agent performs an action, receives a reward or penalty, and learns over time which actions give the best results.
The Q-value estimates the reward available for taking an action in a given state. Through repeated experimentation, Q-values are updated and the agent finds the optimal strategy. It does not need any prior knowledge of the environment.
Importance
- Helps machines train and learn through trial and error.
- Enhances decision-making through continuous feedback.
- Makes it easier for AI to make reliable decisions.
- No predefined model of the environment is required.
Use cases
- Automating workflows within an industry.
- Training robots for specific tasks.
- Allocating and optimizing the distribution of resources.
- Building AI-powered gaming applications.
See it running on your own hardware
Vanik Edge OS runs AI models, agents and apps inside your building, so your data stays there.