can you write the following sentences in better way?: Reinforcement learning is one of the machine learning approaches in which an agent tries to improve its decisions based on interactions with the environment by receiving feedbacks from the results of its decisions in the environment. The main framework of reinforcement learning consists of two components: an agent and its environment. The output of the interactions between the agent and the environment is created in a repetitive cyclical process, a sequence of states, actions and rewards as shown in Figure 1. According to this framework, an intelligent agent performs an action a_t concerning the current state at time t (s_t ) and receives a reward r_(t+1) as a result of the performed action. Then, the agent observes a new state s_(t+1) and performs the next action based on the new state. This iterative framework continues until the agent converges to an optimal policy by maximizing a notion of cumulative reward.

What is Reinforcement Learning?

Reinforcement learning is an area of machine learning in which an agent learns how to interact with its environment in order to maximize a notion of cumulative reward. It is based on a feedback loop of the agent performing an action and then observing the results of that action in the environment, after which they can take another action and repeat the process. This cyclical framework is composed of three components: an agent, its environment, and a sequence of states, actions, and rewards.

How Does Reinforcement Learning Work?

Reinforcement learning is based on a feedback loop between the agent and its environment. The agent performs an action a_t concerning the current state at time t (s_t ) and receives a reward r_(t+1) as a result of the performed action. Then, the agent observes a new state s_(t+1) and performs the next action based on the new state. This iterative framework continues until the agent converges to an optimal policy by maximizing a notion of cumulative reward.

What are the Components of Reinforcement Learning?

The main components of reinforcement learning are the agent, its environment, and the sequence of states, actions, and rewards. The agent is the entity which interacts with its environment, performing actions and observing the results. The environment is the space in which the agent is interacting, and the sequence of states, actions, and rewards is the feedback loop of the agent performing an action, observing the results of that action, and then taking another action.

What is the Goal of Reinforcement Learning?

The goal of reinforcement learning is for the agent to converge to an optimal policy by maximizing a notion of cumulative reward. This is achieved by performing actions and observing their results, and then using the rewards received to adjust its behavior and find the optimal policy.

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