Why all problems are not in P complexity? İf Somebody wants to play perfect chess.I consider for finding solution to this problem,possible minimum data compression method which describes with 10 bit maximum possible data is in the range of 2^10.Then with some formula which can take input as next move in the chess,There should be some formula that can change all equations which are in the chess solving algorithm.Therefore ,if we assume in the chess.There should be 10^120 possible games.With approximately 400 bit with if conditions we can calculate all possible game's best strategy and with same thinking way all math problems can be solved with P complexity.Why there are differences with complexity classes?Short answer:İn karnaugh map some variation cannot be described shortly.
I understood my mistake vote to delete.
Chess is a fixed, finite problem. Because there's no input, you can solve it in a constant amount of time.

Computational complexity considers problems with inputs and looks at how the cost of the computation increases as the input gets longer. For example, you could generalize chess from an $8\times 8$ board to an arbitrary $n\times n$ board and ask how the time taken to compute which side can force checkmate varies as a function of&nbsp;$n$.  Certain versions of this problem (it depends on exactly what rules you take) have been proven to require an amount of time that is exponential in&nbsp;$n$, which implies that they can't be solved in only a polynomial amount of time.