INNER CODE UNIT · Python

on_reset

rlcode/reinforcement-learning · 1-grid-world/1-policy_iteration.py:114

    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()

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