agent.md

Agent() :

Field Summary:

Type	Field
float	Learning rate
float	Gamma
int	Number of actions
float	Epsilon
int	batch size
int	input dimensions
float	epsilon end
int	memory size
string	model save name

Constructor Summary

Agent(gamma, epsilon, lr, input_dims, n_actions, mem_size, batch_size, epsilon_end)

Agent.choose_action():

Field Summary:

Type	Field
environment variables (depends on what you are trading the agent on)	observation

Constructor Summary

Agent.choose_action(observation)

Agent.store_transition():

Field Summary:

Type	Field
float	state
float	action
float	reward
float	new state
bool	done

Constructor Summary

Agent.store_transition(state, action, reward, new_state, done)

Agent.learn():

Field Summary:

Description
Runs the data is has collected through the neural network

Constructor Summary

Agent.learn()

Agent.save_model:

Field Summary:

Description
saves the model

Constructor Summary

Agent.save_model()

Agent.load_model:

Field Summary:

Description
loads the model

Constructor Summary

Agent.loads_model()