Showing 2 of total 2 results (show query)
mhahsler
pomdp:Infrastructure for Partially Observable Markov Decision Processes (POMDP)
Provides the infrastructure to define and analyze the solutions of Partially Observable Markov Decision Process (POMDP) models. Interfaces for various exact and approximate solution algorithms are available including value iteration, point-based value iteration and SARSOP. Smallwood and Sondik (1973) <doi:10.1287/opre.21.5.1071>.
Maintained by Michael Hahsler. Last updated 4 months ago.
control-theorymarkov-decision-processesoptimizationcpp
19 stars 7.03 score 21 scriptsmhahsler
markovDP:Infrastructure for Discrete-Time Markov Decision Processes (MDP)
Provides the infrastructure to work with Markov Decision Processes (MDPs) in R. The focus is on convenience in formulating MDPs, the support of sparse representations (using sparse matrices, lists and data.frames) and visualization of results. Some key components are implemented in C++ to speed up computation. Several popular solvers are implemented.
Maintained by Michael Hahsler. Last updated 15 days ago.
control-theorymarkov-decision-processoptimizationcpp
7 stars 5.51 score 4 scripts