Uses of Class
jmarkov.basic.Solution

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()