opponent scored a goal then our agent will receive a penalty of minus 1 and the entire goal of the agent is to optimize its policy to receive as much reward as possible so in order to train our policy network the first thing we're gonna do is collect a bunch of experience so you're just gonna run a whole bunch of those game frames through your network select random actions feed them back into the engine and just create a whole bunch of random pong games and now obviously since our agent hasn't learned anything useful yet it's