compute_plus_policy: compute_plus_policy
In boettiger-lab/pomdpplus: Planning and Learning in Uncertain Systems

Description Usage Arguments Value Examples

View source: R/compute_plus_policy.R

compute_plus_policy

1 2	compute_plus_policy(alphas, models, model_prior = NULL, state_prior = NULL, a0 = 1)

`alphas`	the alpha vectors for each model, as provided from `sarsop_plus`, which will otherwise be run each time if not provided.
`models`	a list of lists, each of which gives the transition matrix, observation matrix and reward matrix for the model considered
`model_prior`	Prior belief assigned to each model. uniform by default.
`state_prior`	Prior belief that system is in state x_i and model m_i
`a0`	initial action (used to make the first observation, only relevant if observation depends on action)

a data frame containing the policy and value associated with each possible observation

## Not run: 
source(system.file("examples/K_models.R", package="pomdpplus"))
alphas <- sarsop_plus(models, discount, precision = 1)
unif <- compute_plus_policy(alphas, models)

## End(Not run)