INNER CODE UNIT · Python
on_move
rlcode/reinforcement-learning · 1-grid-world/1-policy_iteration.py:111
def on_move():
display.move_along_policy(policy_iteration.get_action)
def on_reset():
policy_iteration.__init__(env)
display.clear()
display.agent_pos = [0, 0]
display.clicks.clear()
# Workflow: (Evaluate x several -> Improve) x several -> Move.
# Improve unlocks after Evaluate; Move unlocks after Improve.
display.buttons = [
("Evaluate", on_evaluate),
("Improve", on_improve, lambda: display.click_count("Evaluate") > 0),
("Move", on_move, lambda: display.click_count("Improve") > 0),
("Reset", on_reset),
]
display.mainloop()