|
||||||||||
PREV NEXT | FRAMES NO FRAMES |
Packages that use Solution | |
---|---|
jmarkov.jmdp | jMDP is used to solve Markov Decision Processes. |
jmarkov.jmdp.solvers | This package contins the framwork of solvers used by jMDP to solve Markov Decision Processes. |
Uses of Solution in jmarkov.jmdp |
---|
Methods in jmarkov.jmdp that return Solution | |
---|---|
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 |
Uses of Solution in jmarkov.jmdp.solvers |
---|
Methods in jmarkov.jmdp.solvers that return Solution | |
---|---|
abstract Solution<S,A> |
MpsLpDiscountedSolver.buildSolution()
The implementator classes should override this class to build the solution after the model has been solved. |
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> |
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()
|
|
||||||||||
PREV NEXT | FRAMES NO FRAMES |