Info about the actions in the HMDP model under consideration.

Usage

getBinInfoActions(
  prefix = "",
  labels = TRUE,
  fileA = "actionIdx.bin",
  filePr = "transProb.bin",
  fileW = "actionWeight.bin",
  fileLabelW = "actionWeightLbl.bin",
  fileLabelA = "actionIdxLbl.bin"
)

Arguments

prefix: A character string with the prefix added to til binary files.
labels: Should labels be extracted.
fileA: The binary file containing the description of actions.
filePr: The binary file containing the description of transition probabilities.
fileW: The binary file containing the description of weights.
fileLabelW: The binary file containing the weight labels.
fileLabelA: The binary file containing the action labels.

Value

A data frame with the information. Scope string contain the scope of the transitions and can be 4 values:

0: A transition to the next stage in the father process,
1: A transition to next stage in the current process,
2: A transition to a child process (stage zero in the child process),
3: A transition to the state with sId = idx is considered.

The index string denote the index (id is scope = 3) of the state at the next stage.

Note

The model don't have to be loaded, i.e only read the binary files. The state id (sId) will not be the same as in the loaded model!

Examples

## Use temp dir
wd <- setwd(tempdir())

# Create a small HMDP with two levels
w<-binaryMDPWriter()
w$setWeights(c("Duration","Net reward","Items"))
w$process()
   w$stage()
      w$state(label="M0")
         w$action(label="A0",weights=c(0,0,0),prob=c(2,0,1))
            w$process()
               w$stage()
                  w$state(label="D")
                     w$action(label="A0",weights=c(0,0,1),prob=c(1,0,0.5,1,1,0.5))
                     w$endAction()
                  w$endState()
               w$endStage()
               w$stage()
                  w$state(label="C0")
                     w$action(label="A0",weights=c(0,0,0),prob=c(1,0,1))
                     w$endAction()
                     w$action(label="A1",weights=c(1,2,1),prob=c(1,0,0.5,1,1,0.5))
                     w$endAction()
                  w$endState()
                  w$state(label="C1")
                     w$action(label="A0",weights=c(0,0,0),prob=c(1,0,1))
                     w$endAction()
                     w$action(label="A1",weights=c(1,2,1),prob=c(1,0,0.5,1,1,0.5))
                     w$endAction()
                  w$endState()
               w$endStage()
               w$stage()
                  w$state(label="C0")
                     w$action(label="A0",weights=c(1,4,0),prob=c(0,0,1))
                     w$endAction()
                  w$endState()
                  w$state(label="C1")
                     w$action(label="A0",weights=c(1,4,0),prob=c(0,0,1))
                     w$endAction()
                  w$endState()
               w$endStage()
            w$endProcess()
         w$endAction()
         w$action(label="A1",weights=c(0,0,0),prob=c(2,0,1))
            w$process()
               w$stage()
                  w$state(label="D")
                     w$action(label="A0",weights=c(0,0,1),prob=c(1,0,1))
                     w$endAction()
                  w$endState()
               w$endStage()
               w$stage()
                  w$state(label="C0")
                     w$action(label="A0",weights=c(0,0,0),prob=c(1,0,1))
                     w$endAction()
                     w$action(label="A1",weights=c(1,2,1),prob=c(1,0,0.5,1,1,0.5))
                     w$endAction()
                  w$endState()
               w$endStage()
               w$stage()
                  w$state(label="C0")
                     w$action(label="A0",weights=c(1,4,0),prob=c(0,0,1))
                     w$endAction()
                  w$endState()
                  w$state(label="C1")
                     w$action(label="A0",weights=c(1,4,0),prob=c(0,0,1))
                     w$endAction()
                     w$action(label="A1",weights=c(0,10,5),prob=c(0,0,0.5,0,1,0.5))
                     w$endAction()
                  w$endState()
               w$endStage()
            w$endProcess()
         w$endAction()
      w$endState()
      w$state(label="M1")
         w$action(label="A0",weights=c(0,0,0),prob=c(2,0,1))
            w$process()
               w$stage()
                  w$state(label="D")
                     w$action(label="A0",weights=c(0,0,1),prob=c(1,0,0.5,1,1,0.5))
                     w$endAction()
                  w$endState()
               w$endStage()
               w$stage()
                  w$state(label="C0")
                     w$action(label="A0",weights=c(0,0,0),prob=c(1,0,1))
                     w$endAction()
                  w$endState()
                  w$state(label="C1")
                     w$action(label="A0",weights=c(0,0,0),prob=c(1,0,1))
                     w$endAction()
                  w$endState()
               w$endStage()
               w$stage()
                  w$state(label="C0")
                     w$action(label="A0",weights=c(1,4,0),prob=c(0,0,1))
                     w$endAction()
                  w$endState()
                  w$state(label="C1")
                     w$action(label="A0",weights=c(1,4,0),prob=c(0,0,1))
                     w$endAction()
                  w$endState()
               w$endStage()
            w$endProcess()
         w$endAction()
      w$endState()
   w$endStage()
w$endProcess()
w$closeWriter()
#> 
#>   Statistics:
#>     states : 16 
#>     actions: 21 
#>     weights: 3 
#> 
#>   Closing binary MDP writer.
#> 

## Info about the binary files (don't have to load the model first)
getBinInfoStates()
#> # A tibble: 16 × 3
#>      sId stageStr  label
#>    <dbl> <chr>     <chr>
#>  1     0 0,0       M0   
#>  2     1 0,0,0,0,0 D    
#>  3     2 0,0,0,1,0 C0   
#>  4     3 0,0,0,1,1 C1   
#>  5     4 0,0,0,2,0 C0   
#>  6     5 0,0,0,2,1 C1   
#>  7     6 0,0,1,0,0 D    
#>  8     7 0,0,1,1,0 C0   
#>  9     8 0,0,1,2,0 C0   
#> 10     9 0,0,1,2,1 C1   
#> 11    10 0,1       M1   
#> 12    11 0,1,0,0,0 D    
#> 13    12 0,1,0,1,0 C0   
#> 14    13 0,1,0,1,1 C1   
#> 15    14 0,1,0,2,0 C0   
#> 16    15 0,1,0,2,1 C1   
getBinInfoActions()
#> # A tibble: 21 × 9
#>      aId   sId scope index pr      Duration `Net reward` Items label
#>    <dbl> <int> <chr> <chr> <chr>      <dbl>        <dbl> <dbl> <chr>
#>  1     0     0 2     0     1              0            0     0 A0   
#>  2     1     1 1,1   0,1   0.5,0.5        0            0     1 A0   
#>  3     2     2 1     0     1              0            0     0 A0   
#>  4     3     2 1,1   0,1   0.5,0.5        1            2     1 A1   
#>  5     4     3 1     0     1              0            0     0 A0   
#>  6     5     3 1,1   0,1   0.5,0.5        1            2     1 A1   
#>  7     6     4 0     0     1              1            4     0 A0   
#>  8     7     5 0     0     1              1            4     0 A0   
#>  9     8     0 2     0     1              0            0     0 A1   
#> 10     9     6 1     0     1              0            0     1 A0   
#> # ℹ 11 more rows

## reset working dir
setwd(wd)