Author(s): Cornellius Yudha Wijaya
Originally published on Towards AI.
Learn the reinforcement learning hands-on with these packages
Photo by Tinky Delta on Unsplash
Reinforcement Learning is a machine learning study field with concerns about optimal decision-making. By learning from the environment, Reinforcement Learning would find the parameter that maximizes rewards.
Unlike supervised or unsupervised learning, Reinforcement Learning uses an independent learner (agent) to learn the environment without any labels or directions. The learner must follow specific policies and reward systems set before learning.
Essentially, Reinforcement Learning requires four elements:
LearnerEnvironmentPolicy ActionReward
In general, there would be a valuable function in which the algorithm would try to maximize the reward average from learning the environment based on the action.
It might not sound very… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI