I need Python code using q$-$learning$/$QTables to choose an action. I need it to use gymnasium to do a Frozen Lake with a success rate of $100\%$for nonslippery and $40\%$at least for slippery. The board should be an $8$x$8$ and random. The code should have options to turn on render and set slippery to true or false. The success rate should be printed after the run. Ideas I had was to track the state $(0-63)$ and if the $($state $<$ new$\_$state$)+1$ reward. $($state $>$ new$\_$state$)-1$ reward. Frozen Lake Falls would be $-3$ and the goal is $+10.$