Package | Description |
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jmarkov.jmdp |
jMDP is used to solve Markov Decision Processes.
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jmarkov.jmdp.solvers |
This package contins the framwork of solvers used by jMDP to solve Markov Decision Processes.
|
Modifier and Type | Method and Description |
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Solution<S,A> |
DTMDP.solve(double interestRate)
Solves the problem with the given interest rate
|
Solution<S,A> |
CTMDP.solve(double interestRate)
Solves the problem with the given interest rate
|
Modifier and Type | Method and Description |
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Solution<S,A> |
MPSXpressDiscounted.buildSolution()
A solution provided for a MPS File by Xpress-Optmizer has the
next framework.
|
Solution<S,A> |
MPSXpressAverage.buildSolution() |
Solution<S,A> |
MPSQsOptDiscountedSolver.buildSolution() |
Solution<S,A> |
MPSQsOptAverageSolver.buildSolution() |
abstract Solution<S,A> |
MpsLpDiscountedSolver.buildSolution()
The implementator classes should override this class to build
the solution after the model has been solved.
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Solution<S,A> |
LPSolver.buildSolution()
The implementator classes should override this class to build
the solution after the model has been solved.
|
Solution<S,A> |
LPBCLDiscountedSolver.buildSolution() |
Solution<S,A> |
ValueIterationSolver.solve()
Solves the problem.
|
Solution<S,A> |
StochasticShortestPathSolver.solve() |
abstract Solution<S,A> |
Solver.solve()
Called to solve the problem.
|
Solution<S,A> |
RelativeValueIterationSolver.solve() |
Solution<S,A> |
PolicyIterationSolverAvg.solve() |
Solution<S,A> |
PolicyIterationSolver.solve() |
Solution<S,A> |
MpsLpDiscountedSolver.solve() |
Solution<S,A> |
MpsLpAverageSolver.solve() |
Solution<S,A> |
LPBCLDiscountedSolver.solve() |
Solution<S,A> |
LPBCLAverageSolver.solve()
Linear Programming Average Solver is a tool that builds the
solution based on the MDP's mathematical background given by
Puterman and the software provided by XpressMP (BCL libraries).
|
Solution<S,A> |
FiniteSolver.solve() |