Let me defines somethings :
Let $0<x<1$ let $f(x)$ be the function : $$f(x)=\exp\Big(\frac{x-1}{x}\ln(3)\Big)$$ And : $$g(x)=f(1-x)$$ Denote by : $$\min_{x\in(0,1)}(f(x)+g(x))=\frac{2}{3}$$ Define $f^n(x)$ by ($n\geq2$ a natural number): $$f^n(x)=\underbrace{f(f(f(f(\cdots(x)\cdots)}_{n \quad \text{times}}$$ And $g^n(x)$ by : $$g^n(x)=g(\underbrace{g(1-g(1-g(1-g(\cdots g(1-x))\cdots)}_{(n-1) \quad \text{times}}$$ Then we have $$\min_{x\in(0,1)}(f^n(x)+g^n(x))=\frac{2}{3}$$
Let me show $$\min_{x\in(0,1)}(f(x)+g(x))=\frac{2}{3}$$
The derivative is :
$$f'(x)+g'(x)= 3^{\frac{(x - 1)}{x}} \Big(\frac{1}{x} - \frac{(x - 1)}{x^2}\Big) \log(3) + 3^{\frac{-x}{1-x}} \Big(-\frac{x}{(1 - x)^2} - \frac{1}{(1 - x)}\Big) \log(3)$$
Or :
$$f'(x)+g'(x)=\frac{\Big(3^{\frac{(x - 1)}{x}} (x - 1)^2 - 3^{\frac{-x}{1-x}} x^2\Big) \log(3)}{((x - 1)^2 x^2)}$$
Now it's not hard to show that the derivative vanishes at $x=0.5$ and get the desired result using the closed interval method .
For the other cases I believe that there is a trick or somethings like that .
Thanks a lot for your time and patience .
Ps:I think furthermore that we can replace the value $\ln(3)$ be something more general $\ln(\alpha)$ by example with $\alpha\geq 2$ .
In the following I will use a subscript notation $f_n, g_n$ instead of the given superscript one as it might lead to confusion regarding the exponentiation.
At first one needs to note that the direct definitions of $f_n, g_n$ can be rewritten in terms of recursive definitions. For $f_n$ it is rather obvious $f_n(x) = f(f_{n-1}(x))$ whereas for $g_n$ it might help to write down the first couple of terms \begin{align*} g_2(x) &:= g(g(1-x)) = g(f(x)) \\ &= g(f_1(x)) \\ g_3(x) &:= g(g(1-g(1-x)))= g(g(1-f(x)))= g(f(f(x))) \\ &= g(f_2(x)) \\ g_4(x) &:= g(g(1-g(1-g(1-x)))) \\ &= g(f_3(x)) \end{align*} which gives the general recursive formula $$ g_n(x) = g(f_{n-1}(x)) \,. $$ (To be exact I definied $f_1 := f$.)
Next we need to differentiate $f_n+g_n$ to find its extrema \begin{align*} (f_n(x)+g_n(x))' &= f_n'(x)+g_n'(x) \\ &= (f(f_{n-1}(x)))' + (g(f_{n-1}(x)))' \\ &= f'(f_{n-1}(x)) \cdot f_{n-1}'(x) + g'(f_{n-1}(x)) \cdot f_{n-1}'(x) \\ &= f_{n-1}'(x) \left[ f'(f_{n-1}(x)) + g'(f_{n-1}(x)) \right] \\ &= f_{n-1}'(x) \left[ f'(y) + g'(y) \right] \,, \qquad y := f_{n-1}(x) \\ &\overset{!}{=} 0 \end{align*} where I introduced the definition of $y$ to make it more obvious that both terms in the sum depend on the same variable.
As $f_{n-1}'(x) \neq 0$ we need to solve $$ 0 = f'(y) + g'(y) $$ and the solution $y=y_0=\frac{1}{2}$ has been shown in the first part.
Compute the extremal value ($x_0$ refers to $y_0=f_{n-1}(x_0)$) \begin{align*} f_n(x_0)+g_n(x_0) &= f(y_0)+g(y_0) = \frac{2}{3} \end{align*} where the summation value follows from the first part.
For the argument to be complete note that $f$ is one-to-one. The same goes for $f_n$.
Is it still a minima (we only showed that its derivative is zero at $x_0$)?
Note that $f_n+g_n$ is continuous and the limit for $x\rightarrow0^+$ is easily computed to be 1. Thus, it it still a minima.