👉 Reinforcer or Reinforcement is a type of reinforcement learning (RL) algorithm that has been used in the field of machine learning to optimize the performance of deep neural networks. The goal of this algorithm is to find an optimal policy for a given task, where the agent learns to make decisions and choose actions based on the rewards it receives from its environment.
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What is the definition of Reinforcers? 🙋
👉 Reinforcement Learning is a type of machine learning where an agent learns to make decisions based on rewards and punishments. The goal is for the agent to maximize its reward by choosing actions that lead to better outcomes in future trials, or "reinforcement." Reinforcement Learning has been applied in a variety of fields such as robotics, finance, game playing, etc.
What is the definition of Reinforcer? 🙋
👉 In behavioral psychology, a reinforcer is an external stimulus that provides a positive reinforcement to a behavior. Reinforcers can be physical objects like food or toys, rewards like praise or money, or even simple actions such as smiling or nodding. The goal of reward systems is to increase the frequency and intensity of desirable behaviors through continuous reinforcement.
