`expo_decay()`

can be used to increase or decrease a function exponentially
over iterations. This can be used to dynamically set parameters for
acquisition functions as iterations of Bayesian optimization proceed.

## Arguments

- iter
An integer for the current iteration number.

- start_val
The number returned for the first iteration.

- limit_val
The number that the process converges to over iterations.

- slope
A coefficient for the exponent to control the rate of decay. The sign of the slope controls the direction of decay.

## Details

Note that, when used with the acquisition functions in `tune()`

, a wrapper
would be required since only the first argument would be evaluated during
tuning.