Reinforcement Learning (RL) is a unique subset of machine learning where an agent learns by interacting with an environment. Unlike supervised learning, RL does not rely on labeled datasets. Instead, it employs a reward-based system where the agent receives feedback (positive rewards for desired actions and penalties for suboptimal ones). Through trial and error, the agent aims to maximize its cumulative reward over time by discovering the best policy. For instance, RL is used in robotics to enable autonomous movement, in gaming AI (e.g., AlphaGo), and in resource management (e.g., optimizing energy grids). The agent’s learning occurs iteratively, using algorithms like Q-learning or policy gradients, making it essential for dynamic decision-making tasks in uncertain environments. Why Other Options Are Incorrect:
Phenyl mercuric acetate (PMA) is a ______ of antitranspirant.
Bean common mosaic disease is caused by
In rust cycle, wheat is infected by which of the following spores?
Relatively more hygroscopic fertilizer is:
What is the inflorescence of sugarcane?
Grubs of Holotrichia consanguinea feed on
Ribboning is process of peeling out raw bark from the green plant immediately after harvest is done in which fibre crop?
In paddy, the clipping of tip of seedlings is done as a preventive measure against which pest?
The short range forecasting is issued twice a day and is valid for ………………………
The law that determines the best uses of limited resources among alternative uses is known as: