Intermediate · Reinforcement Learning

Reward

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. A feedback signal in reinforcement learning, indicating the desirability of an agent's action in a given state.

Technical Definition

A feedback signal in reinforcement learning, indicating the desirability of an agent's action in a given state.

How it works

In reinforcement learning, a reward is a scalar feedback signal provided by the environment to the agent after it performs an action. Positive rewards encourage desirable behaviors, while negative rewards (penalties) discourage undesirable ones. The agent's ultimate objective is to maximize the total cumulative reward it receives over time.

Related Concepts

• Reinforcement Learning — A paradigm where an agent learns to make decisions by receiving rewards or penalties from its environment through trial and error.
• AI Agent — An AI system that autonomously plans, uses tools, and takes actions to accomplish goals through iterative reasoning.
• Policy — In reinforcement learning, the strategy an agent follows to choose actions given a state.