<jupyter_start><jupyter_text>Cube 2x2 zero goal fix<jupyter_code>df_c2_zg = pd.read_csv("../csvs/c2x2-zero-goal-d200-t1.csv")
df_c2_zg_fix = pd.read_csv("../csvs/c2x2-zero-goal-d200-t1-v2.csv")
sns.lineplot('depth', 'duration', data=df_c2_zg);
sns.lineplot('depth', 'duration', data=df_c2_zg_fix);
sns.lineplot('depth', 'is_solved', data=df_c2_zg);
sns.lineplot('depth', 'is_solved', data=df_c2_zg_fix);
sns.lineplot('depth', 'is_solved', data=df_fix);
sns.lineplot('depth', 'is_solved', data=df_c2_zg_fix);
sns.lineplot('depth', 'solve_steps', data=df_c2_zg);
sns.lineplot('depth', 'solve_steps', data=df_c2_zg_fix);
sns.lineplot('depth', 'solve_steps', data=df_fix);
sns.lineplot('depth', 'solve_steps', data=df_c2_zg_fix);
sns.lineplot('depth', 'solve_steps', data=df_fix[df_fix.is_solved==1]);
sns.lineplot('depth', 'solve_steps', data=df_c2_zg_fix[df_c2_zg_fix.is_solved==1]);<jupyter_output><empty_output><jupyter_text>Significant improvement with the fix.  Cube 3x3, paper method<jupyter_code>df_c3_p = pd.read_csv("../csvs/c3x3-paper-d200-t1.csv")
df_c3_p_fix = pd.read_csv("../csvs/c3x3-paper-d200-t1-v2.csv")
sns.lineplot('depth', 'duration', data=df_c3_p);
sns.lineplot('depth', 'duration', data=df_c3_p_fix);
sns.lineplot('depth', 'is_solved', data=df_c3_p);
sns.lineplot('depth', 'is_solved', data=df_c3_p_fix);
sns.lineplot('depth', 'solve_steps', data=df_c3_p);
sns.lineplot('depth', 'solve_steps', data=df_c3_p_fix);<jupyter_output><empty_output><jupyter_text>No improvement  Cube 3x3, zero goalCompare previous results with fixed (which gave more steps to solve for each cube)<jupyter_code>df_c3_zg = pd.read_csv("../csvs/c3x3-zero-goal-d200-t1.csv")
df_c3_zg_fix = pd.read_csv("../csvs/c3x3-zero-goal-d200-t1-v2.csv")
sns.lineplot('depth', 'duration', data=df_c3_zg);
sns.lineplot('depth', 'duration', data=df_c3_zg_fix);
sns.lineplot('depth', 'is_solved', data=df_c3_zg);
sns.lineplot('depth', 'is_solved', data=df_c3_zg_fix);
sns.lineplot('depth', 'solve_steps', data=df_c3_zg);
sns.lineplot('depth', 'solve_steps', data=df_c3_zg_fix);
sns.lineplot('depth', 'solve_steps', data=df_c3_zg[df_c3_zg.is_solved==1]);
sns.lineplot('depth', 'solve_steps', data=df_c3_zg_fix[df_c3_zg_fix.is_solved==1]);<jupyter_output><empty_output><jupyter_text>No improvement versus old version  Cube 3x3, paper method versus zero goalCompare fixed results on paper with fixed in my method<jupyter_code>sns.lineplot('depth', 'duration', data=df_c3_p_fix);
sns.lineplot('depth', 'duration', data=df_c3_zg_fix);
sns.lineplot('depth', 'is_solved', data=df_c3_p_fix);
sns.lineplot('depth', 'is_solved', data=df_c3_zg_fix);
sns.lineplot('depth', 'solve_steps', data=df_c3_p_fix);
sns.lineplot('depth', 'solve_steps', data=df_c3_zg_fix);<jupyter_output><empty_output><jupyter_text>No much improvements. Probably, steps limit is too small.  Cube 3x3, zero goal trained with decay and withoutCompare policies obtained from training with LR decay and without it<jupyter_code>df_c3_nodecay = pd.read_csv("../csvs/c3x3-zero-goal-d200-no-decay-v2.csv")
df_c3_decay = pd.read_csv("../csvs/c3x3-zero-goal-d200-t1-v2.csv")
sns.lineplot('depth', 'duration', data=df_c3_nodecay);
sns.lineplot('depth', 'duration', data=df_c3_decay);
sns.lineplot('depth', 'is_solved', data=df_c3_nodecay);
sns.lineplot('depth', 'is_solved', data=df_c3_decay);
sns.lineplot('depth', 'solve_steps', data=df_c3_nodecay);
sns.lineplot('depth', 'solve_steps', data=df_c3_decay);<jupyter_output><empty_output>
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