Question

What is the parameter of analysis in reinforcement learning?

(a) Number of requests during wake cycle

(b) Number of processes to achieve final outcome

(c) Degree of failure

(d) Degree of success

This question was addressed to me during an online exam.

The above asked question is from Next Generation Wireless Network topic in portion Next Generation Wireless Network of Cognitive Radio

Answer 1

The correct answer is:

(d) Degree of success

Explanation: In reinforcement learning (RL), the key parameter of analysis is typically the "degree of success" in achieving a specific task or goal. This success is measured through the concept of rewards and penalties (or negative rewards), where the learning agent aims to maximize the cumulative reward over time. The degree of success in RL directly refers to how effectively the agent learns to perform its task by interacting with the environment and improving its policy based on feedback.

In the context of cognitive radio or next-generation wireless networks, RL can be applied to optimize network performance based on feedback and success in achieving network goals like throughput, latency, or spectrum efficiency.