ai with python reinforcement learning in this you will learn in detail about the concepts reinforcement learning in ai with python basics of reinforcement learning this type of learning is used to reinforce or strengthen the network based on critic information that isa network being trained under reinforcement learningreceives some feedback from the environment howeverthe feedback is evaluative and not instructive as in the case of supervised learning based on this feedbackthe network performs the adjustments of the weights to obtain better critic information in future this learning process is similar to supervised learning but we might have very less information the following figure gives the block diagram of reinforcement learningx (inputneural network (actual outputerror signal error signal generator (reinforcement signalbuilding blocksenvironment and agent environment and agent are main building blocks of reinforcement learning in ai this section discusses them in detailagent an agent is anything that can perceive its environment through sensors and acts upon that environment through effectors human agent has sensory organs such as eyesearsnosetongue and skin parallel to the sensorsand other organs such as handslegsmouthfor effectors robotic agent replaces cameras and infrared range finders for the sensorsand various motors and actuators for effectors software agent has encoded bit strings as its programs and actions