getBinInfoActions: Info about the actions in the HMDP model under consideration.

In MDP2: Markov Decision Processes (MDPs)

Info about the actions in the HMDP model under consideration.

Description

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()

## Info about the binary files (don't have to load the model first)
getBinInfoStates()
getBinInfoActions()

## reset working dir
setwd(wd)

MDP2 documentation built on June 13, 2026, 1:08 a.m.