What is reward?
A feedback signal given to an agent for taking a particular action
reward explained in plain English
In artificial intelligence, a reward is a way to tell an agent whether its actions are good or bad. It's like giving a sticker to a child for doing something right. The agent uses this feedback to learn and improve its behavior over time.
Analogy
Think of a reward like a treat given to a dog for sitting on command. The dog learns to associate sitting with getting a treat, so it's more likely to sit in the future.
Example
Self-driving cars use rewards to learn how to navigate roads safely. For example, a car might receive a reward for staying in its lane and avoiding obstacles.
How is reward used?
Rewards are used in reinforcement learning, a type of machine learning where an agent learns by interacting with an environment and receiving feedback in the form of rewards or penalties.
Common misconceptions about reward
Some people think that rewards are the only thing that matters in reinforcement learning, but the reality is that the agent also needs to balance exploration and exploitation to learn effectively.
History
The concept of rewards in artificial intelligence dates back to the 1950s and 1960s, when researchers like Marvin Minsky and Richard Sutton began exploring ways to teach machines to learn from feedback.
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