Perform policy iteration using the discounted expected-weight Bellman operator on the MDP.

The policy can afterwards be received using functions get_policy and get_policy_w.

Usage

run_policy_ite_discount(
  mdp,
  w,
  dur,
  rate = 0,
  rate_base = 1,
  discount_factor = NULL,
  max_ite = 100,
  discount_method = "continuous",
  objective = c("max", "min"),
  get_log = TRUE
)

Arguments

mdp

The MDP loaded using load_mdp().

w

The label of the weight we optimize.

dur

The label of the duration/time such that discount rates can be calculated.

rate

The interest rate.

rate_base

The time-horizon the rate is valid over.

discount_factor

The discount rate for one time unit. If specified rate and rate_base are not used to calculate the discount rate.

max_ite

Max number of iterations. If the model does not satisfy the unichain assumption the algorithm may loop.

discount_method

Either 'continuous' or 'discrete', corresponding to discount factor exp(-rate/rate_base) or 1/(1 + rate/rate_base), respectively. Only used if discount_factor is NULL.

objective

Optimize by maximizing ("max") or minimizing ("min") the Bellman value.

get_log

Output the log messages.

Value

Nothing.

See also

get_policy().