The Actor-Critic Algorithm is a term from the field of artificial intelligence and automation. It belongs to the advanced methods in so-called reinforcement learning, where computers or robots learn to make decisions independently.<\/p>\n
When it comes to the Actor-Critic algorithm, there are two main components: the \u201eActor\u201c and the \u201eCritic\u201c. The Actor decides which action to take next. The Critic then evaluates how good or bad that decision was. Working together, they continuously improve the system's behaviour through learning.<\/p>\n
A practical example: Imagine a warehouse robot designed to sort goods efficiently. The actor chooses which shelf the robot should head to next. The critic then checks whether this choice has led to faster workflows. If the outcome is positive, the algorithm reinforces such decisions for the future.<\/p>\n
Thanks to the Actor-Critic algorithm, machines can develop better strategies in complex and changing environments \u2013 for example, in modern, automated factories or with autonomous vehicles. This improves efficiency and flexibility, making systems self-learning and adaptable.<\/p>","protected":false},"excerpt":{"rendered":"