R package pomdpSolve - Interface to ‘pomdp-solve’ for Partially
Observable Markov Decision Processes
R package pomdpSolve - Interface to ‘pomdp-solve’ for Partially
Observable Markov Decision Processes
Provides pomdp-solve (Cassandra, 2015) to solve POMDPs using a variety of algorithms. A convenient interface is provided in package pomdp.
Stable CRAN version: Install from within R with
install.packages("pomdpSolve")Current development version: Install from r-universe.
install.packages("pomdpSolve", repos = "https://mhahsler.r-universe.dev")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] TRUEpomdp_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 -98.5read_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 3setwd(old_wd)The value function is defined by a set of alpha vectors represented as rows in a matrix with \(V\) 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 \(N\), the action \(A\) defined by the policy and then for each observation \(Z_i\) the id (row) of the policy graph node to transition to.
A detailed description of the available solver options can be found here.
To cite package ‘pomdpSolve’ in publications use:
Hahsler M, Cassandra AR (2023). pomdpSolve: Interface to ‘pomdp-solve’ for Partially Observable Markov Decision Processes. R package version 1.0.3, https://github.com/mhahsler/pomdpSolve.
A BibTeX entry for LaTeX users is
@Manual{, title = {pomdpSolve: Interface to ‘pomdp-solve’ for Partially Observable Markov Decision Processes}, author = {Michael Hahsler and Anthony R. Cassandra}, year = {2023}, note = {R package version 1.0.3}, url = {https://github.com/mhahsler/pomdpSolve}, }