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Anthony R. Cassandra [aut, cph]| Title: | Interface to 'pomdp-solve' for Partially Observable Markov Decision Processes |
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| Description: | Installs an updated version of 'pomdp-solve' and provides a low-level interface. Pomdp-solve is a program to solve Partially Observable Markov Decision Processes (POMDPs) using a variety of exact and approximate value iteration algorithms. A convenient R infrastructure is provided in the separate package pomdp. Kaelbling, Littman and Cassandra (1998) <doi:10.1016/S0004-3702(98)00023-X>. |
| Authors: | Michael Hahsler [aut, cph, cre]
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Anthony R. Cassandra [aut, cph] |
| Maintainer: | Michael Hahsler <[email protected]> |
| License: | GPL (>=3) |
| Version: | 1.0.4.1 |
| Built: | 2024-10-25 05:47:29 UTC |
| Source: | https://github.com/mhahsler/pomdpSolve |
Installs an updated version of 'pomdp-solve', a program to solve Partially Observable Markov Decision Processes (POMDPs) using a variety of exact and approximate value iteration algorithms. This package only provides the executable and a few reading routines. A convenient R infrastructure to use the solver is provided in the separate package pomdp (pomdp::pomdp-package).
Solve a POMDP file with pomdp-solve using pomdp_solve().
Read and write files for pomdp-solve (see read_write).
Find the pomdp-solve executable using find_pomdp_solve().
Package pomdp provides more convenient support to
Define a POMDP using pomdp::POMDP
Solve a POMDP using pomdp::solve_POMDP()
Michael Hahsler
Anthony R. Cassandra, pomdp-solve source code GitHub repository, https://github.com/cassandra/pomdp-solve
Find the pomdp-solve executable
to solve Partially Observable Decision Processes (POMDPs) (Kaelbling et al, 1998)
installed by the pomdpSolve package.
find_pomdp_solve()find_pomdp_solve()
This package only provides a direct interface to the executable.
A more convenient and powerful interface is provided by the function
pomdp::solve_POMDP() in package pomdp.
The executable of pomdp-solve in this direct interface needs to be called with
system2() and runs in a separate process. This way, a failure in the solver will not compromise the
R session. pomdp-solve creates files with the value function and
the policy graph (see read_write).
returns the path to the 'pomdp-solve' executable as a string or stops with an error.
Kaelbling, L.P., Littman, M.L., Cassandra, A.R. (1998). Planning and acting in partially observable stochastic domains. Artificial Intelligence. 101 (1–2): 99-134. doi:10.1016/S0004-3702(98)00023-X
Anthony R. Cassandra, pomdp-solve documentation, https://www.pomdp.org/code/
Anthony R. Cassandra, pomdp-solve source code GitHub repository, https://github.com/cassandra/pomdp-solve
read_write
# find the location of the pomdp-solve executable find_pomdp_solve() # get pomdp-solve options system2(find_pomdp_solve(), args = "-h") # an example of how to solve a simple POMDP can be found in the man page # for read_write.# find the location of the pomdp-solve executable find_pomdp_solve() # get pomdp-solve options system2(find_pomdp_solve(), args = "-h") # an example of how to solve a simple POMDP can be found in the man page # for read_write.
This function provides a bare bones interface to run pomdp-solve on a POMDP file. The results can be read with the function provides in read_write.
pomdp_solve(pomdp, options = list(), verbose = TRUE) pomdp_solve_help()pomdp_solve(pomdp, options = list(), verbose = TRUE) pomdp_solve_help()
pomdp |
the POMDP file to solve. |
options |
a list with options for pomdp-solve. |
verbose |
logical; show the program text output? |
Calling solve_pomdp() first cleans results from previous runs and then executes pomdp-solve with the specified options.
The options are specified in options as a list with entries of the form <option> = <value>.
pomdp_solve_help() displays the available options. Note that the leading dash is not used on the option name. For example:
list(method = "grid", epsilon = 0.1) sets the method option to grid and epsilon to 0.1.
Here is a slightly more detailed description of pomdp-solve's options.
nothing
Anthony R. Cassandra, pomdp-solve code and documentation, https://www.pomdp.org/code/
Anthony R. Cassandra, pomdp-solve GitHub repository, https://github.com/cassandra/pomdp-solve
find_pomdp_solve read_write
# display available options pomdp_solve_help() # solve a POMDP file that ships with this package in a temporary directory old_wd <- setwd(tempdir()) file.copy(system.file("tiger.aaai.POMDP", package = "pomdpSolve"), "./tiger.aaai.POMDP") # Example 1: run solver to completion pomdp_solve("tiger.aaai.POMDP", options = list(method = "incprune")) dir() # you can inspect the files with file.show() # read the raw policy graph (-0 means infinite horizon solution) read_pg_file("tiger.aaai-0.pg") # read the raw value function read_alpha_file("tiger.aaai-0.alpha") # Example 2: use method finite grid (point-based algorithm) and save the used belief points pomdp_solve("tiger.aaai.POMDP", options = list(method = "grid", fg_save = TRUE)) dir() read_belief_file("tiger.aaai-0.belief") # Example 3: Stop value iteration after 50 epochs and then continue with a second call pomdp_solve("tiger.aaai.POMDP", options = list(method = "incprune", horizon = 50)) alpha <- read_alpha_file("tiger.aaai-0.alpha") write_terminal_values("terminal.alpha", alpha) pomdp_solve("tiger.aaai.POMDP", options = list(method = "incprune", terminal_values = "terminal.alpha")) # return to the old directory setwd(old_wd)# display available options pomdp_solve_help() # solve a POMDP file that ships with this package in a temporary directory old_wd <- setwd(tempdir()) file.copy(system.file("tiger.aaai.POMDP", package = "pomdpSolve"), "./tiger.aaai.POMDP") # Example 1: run solver to completion pomdp_solve("tiger.aaai.POMDP", options = list(method = "incprune")) dir() # you can inspect the files with file.show() # read the raw policy graph (-0 means infinite horizon solution) read_pg_file("tiger.aaai-0.pg") # read the raw value function read_alpha_file("tiger.aaai-0.alpha") # Example 2: use method finite grid (point-based algorithm) and save the used belief points pomdp_solve("tiger.aaai.POMDP", options = list(method = "grid", fg_save = TRUE)) dir() read_belief_file("tiger.aaai-0.belief") # Example 3: Stop value iteration after 50 epochs and then continue with a second call pomdp_solve("tiger.aaai.POMDP", options = list(method = "incprune", horizon = 50)) alpha <- read_alpha_file("tiger.aaai-0.alpha") write_terminal_values("terminal.alpha", alpha) pomdp_solve("tiger.aaai.POMDP", options = list(method = "incprune", terminal_values = "terminal.alpha")) # return to the old directory setwd(old_wd)
Read and write files for the pomdp-solve executable.
read_alpha_file(file) read_pg_file(file) read_belief_file(file) write_grid_file(file, belief_points, digits = 7) write_terminal_values(file, alpha, digits = 7)read_alpha_file(file) read_pg_file(file) read_belief_file(file) write_grid_file(file, belief_points, digits = 7) write_terminal_values(file, alpha, digits = 7)
file |
name of the file to read from or to write to. |
belief_points |
a numeric matrix with the number of states columns. Rows represent belief points. |
digits |
number of digits used to write files. |
alpha |
a numeric alpha vector with the length of the number of states. |
pomdp-solve uses text format for its input and output. The input is a POMDP file. The outputs are the following.
Value Function
The value function is returned as files with the extension .alpha
in the format:
A V1 V2 V3 ... VN A V1 V2 V3 ... VN ...
Where A is an action number and the V1 through VN are real values
representing the components of a particular vector that has the
associated action. The action number is the 0-based index of
the action as specified in
the input POMDP file. The vector represents the coefficients of a hyperplane
representing one facet of the piecewise linear and convex (PWLC) value
function. Note that the length of the lists needs to be equal to the
number of states in the POMDP.
read_alpha_file() reads the V components from the file and returns a matrix.
Policy Graph
The policy graph is returned as a file with the extension .pg.
Each line of the file represents one node of the policy graph and
its contents are:
N A Z1 Z2 Z3 ... ...
Here N is a node ID giving the node a unique name, numbered sequentially
and lining up with the value function vectors in the
corresponding output .alpha file above.
The A is the action number defined for this node; it is an integer referring
to the the POMDP file actions by its 0-based index number.
These are followed by a list of node IDs, one for each observation. Thus the
list will have a length equal to the number of observations in the POMDP.
This list specifies the transitions in the policy graph. The nth number in
the list will be the index of the node that follows this one when the
observation received is n.
read_pg_file() returns a data.frame with the nodes in the policy graph as rows.
Terminal Values
Terminal values can be specified as a single alpha vector.
Grid-based Solver Specific Files
The grid-based method can write the used belief points do disk (command line option -fg_save). The
file can be read using read_belief_file().
A matrix with belief points can be written using write_grid_file(). This file can be used
Details about the file formats and pomdp-solve can be found in the References section.
See pomdp_solve() for examples.
read_alpha_file() returns the value function (alpha vectors) as a matrix.
read_pg_file() returns the policy graph as a data.frame.
read_belief_file() returns a matrix if the solver wrote a belief file.
write_grid_file() returns nothing.
write_terminal_values() returns nothing.
Anthony R. Cassandra, pomdp-solve documentation, https://www.pomdp.org/code/
find_pomdp_solve