Skip to contents

R package pomdpSolve - Interface to ‘pomdp-solve’ for Partially Observable Markov Decision Processes

Package on CRAN CRAN RStudio mirror downloads Licenser-universe status

Maintainer: Michael Hahsler

Provides pomdp-solve (Cassandra, 2015) to solve POMDPs using a variety of algorithms. A convenient interface is provided in package pomdp.

To cite package ‘pomdpSolve’ in publications use:

Hahsler M, Cassandra AR (2025). “Pomdp: A computational infrastructure for partially observable Markov decision processes.” The R Journal, 16(2), 1-18. ISSN 2073-4859. doi:10.32614/RJ-2024-021 https://doi.org/10.32614/RJ-2024-021.

@Article{,
  title = {Pomdp: A computational infrastructure for partially observable Markov decision processes},
  author = {Michael Hahsler and Anthony R. Cassandra},
  year = {2025},
  journal = {The R Journal},
  volume = {16},
  number = {2},
  pages = {1--18},
  doi = {10.32614/RJ-2024-021},
  issn = {2073-4859},
}

Installation

Stable CRAN version: Install from within R with

install.packages("pomdpSolve")

Current development version: Install from r-universe.

install.packages("pomdpSolve",
    repos = c("https://mhahsler.r-universe.dev",
              "https://cloud.r-project.org/"))

Usage

Solve a POMDP file that ships with this package in a temporary directory and read the solution.

library(pomdpSolve)

old_wd <- setwd(tempdir())
file.copy(system.file("tiger.aaai.POMDP", package = "pomdpSolve"), "./tiger.aaai.POMDP")
## [1] TRUE
pomdp_solve("tiger.aaai.POMDP", options = list(method = "grid"), verbose = FALSE)
dir()
## [1] "tiger.aaai-0.alpha" "tiger.aaai-0.pg"    "tiger.aaai.POMDP"
read_alpha_file("tiger.aaai-0.alpha")
##         V1    V2
## [1,] -98.5  11.5
## [2,] -10.9   6.5
## [3,]   1.9   1.9
## [4,]   6.5 -10.9
## [5,]  11.5 -98.5
read_pg_file("tiger.aaai-0.pg")
##   N A Z1 Z2
## 1 1 2  3  3
## 2 2 1  3  1
## 3 3 1  4  2
## 4 4 1  5  3
## 5 5 3  3  3
setwd(old_wd)

The value function is defined by a set of alpha vectors represented as rows in a matrix with VV components. Each alpha vector corresponds to a node with the same row number in the policy graph. The policy graph represents the policy in the form of a data.frame with one row for each node. Nodes have a node id NN, the action AA defined by the policy and then for each observation ZiZ_i the id (row) of the policy graph node to transition to.

A detailed description of the available solver options can be found here.

References