Contents
How is the DQN used in gym Pong?
The original DQN Agent used the same neural network architecture, for the all 49 games, that takes as an input an 84x84x4 image. The screen images are first processed by three convolutional layers. This allows the system to exploit spatial relationships, and can sploit spatial rule space.
How is the state of an agent represented in Pong?
The state is a representation of what the agent thinks it knows about its environment which allows it to make decisions. An Agent’s environment may be fully or partially observable: in the case of Pong, the environment is fully observable, given that the entire playing area is visible and can be completely accounted for by the input image.
Is there a class of actions in Pong?
This can make assigning credit to a particular action pretty challenging. You can probably tell that there is class of actions in Pong where the Agent is simply keeping up the rally, versus a class of actions which is likely to win the game, which comprises the actions immediately prior to winning a game.
How many actions are there in OpenAI Gym Pong?
There are three actions an Agent (player) can take within the Pong Environment: remaining stationary, vertical translation up, and vertical translation down. However, if we use the method action_space.n we can realize that the Environment has 6 actions: Even though OpenAI Gym Pong Environment has six actions:
How is the Deep Q Network used in reinforcement learning?
Unlike until now we presented a traditional reinforcement learning setup where only one Q-value is produced at a time, the Deep Q-network is designed to produce in a single forward pass a Q-value for every possible action available in the Environment:
How are screen images processed in deep Q Network?
The screen images are first processed by three convolutional layers. This allows the system to exploit spatial relationships, and can sploit spatial rule space. Also, since four frames are stacked and provided as input, these convolutional layers also extract some temporal properties across those frames.