What does "Learning Agents" mean?
Table of Contents
Learning agents are computer programs that can improve their performance over time by learning from their experiences. They are often used in situations where decisions need to be made repeatedly, like in games or auctions.
How Do They Work?
These agents use algorithms, which are sets of rules or instructions, to decide what actions to take. As they play games or engage in tasks, they receive feedback on their actions, allowing them to adjust their strategies and become better over time.
Payments and Incentives
In some cases, learning agents can use money to influence the behavior of other agents. By making payments to others, a player can encourage cooperation or change the way others act in the game. This can lead to better outcomes for all players involved, as everyone may benefit from the adjusted strategies.
Safety in Learning
When learning agents are put in situations with rules or safety concerns, it can be tricky to ensure they don't take harmful actions. To address this, some methods focus on comparing the agent's decisions to a safe, standard approach. This means that agents are only penalized for harmful actions they cause, making it easier for them to learn while still staying within safe limits.
Practical Uses
Learning agents are used in various fields, from online shopping to robotics. They help improve processes, make better decisions, and adapt to changing environments while keeping safety in mind.