Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min
1,0.0,1.0,1117.0,1117.0,1117.0,1117.0,1.0,,,0.0,,,,,,,,,,,,,,,,,,,
2,205.0,0.0,1937.0,1937.0,820.0,1937.0,0.9992620000000244,-21.0,-21.0,0.0,,,,0.011010780938079,0.013098460400306485,0.06118807196617127,6.86898929416202e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.08733994,0.06833449,0.47135752,0.016372742,,,,
3,413.0,0.0,2768.0,2768.0,831.0,2768.0,0.9985141000000488,-21.0,-21.0,0.0,,,,0.01163802880151147,0.013571124716079436,0.08714678883552551,3.9931001083459705e-05,0.00010000000000000003,2.7105054312137605e-20,0.0001,0.0001,0.06724033,0.035371285,0.2241408,0.011829718999999999,0.10583201,0.011610512,0.12072124,0.08555735
4,667.0,0.0,3783.0,3783.0,1015.0,3783.0,0.9976006000000791,-20.0,-20.0,0.0,,,,0.01136319609350886,0.012043113812065086,0.049625951796770096,9.354137000627816e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.060902383,0.032815605,0.17838788,0.015925674,0.0978057,0.014090337,0.123560354,0.07580207
5,947.0,0.0,4906.0,4906.0,1123.0,4906.0,0.9965899000001124,-18.0,-18.0,0.0,,,,0.010341535720908724,0.011934284708938809,0.06498207896947861,6.708659930154681e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.054970358,0.03215441,0.26232755,0.009252935,0.09154041,0.009532932,0.10656521,0.07300271