Package | Description |
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jmarkov.basic |
This package contains basic elements such as State, Event, Action that are used in jMarkov and jMDP
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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.
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Modifier and Type | Method and Description |
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ValueFunction<S> |
Solution.getValueFunction()
Returns the valueFunction.
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Constructor and Description |
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Solution(ValueFunction<S> valueFunction,
Policy<S,A> policy)
Builds a solution given a value funtcion and a policy
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ValueFunction(ValueFunction<S> vf)
Creates a value function from another given value function
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ValueFunction(ValueFunction<S> vf,
java.lang.String name)
Creates a value function from another given value function
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Modifier and Type | Method and Description |
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ValueFunction<S> |
MDP.getOptimalValueFunction()
Returns the optimal ValueFunction.
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ValueFunction<S> |
DTMDP.getSteadyStateProbabilities() |
ValueFunction<S> |
CTMDP.getSteadyStateProbabilities() |
Modifier and Type | Method and Description |
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ValueFunction<S> |
ValueIterationSolver.getBias() |
ValueFunction<S> |
PolicyIterationSolverAvg.getBias() |
ValueFunction<S> |
Solver.getOptimalValueFunction()
Gets the optimal ValueFunction.
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ValueFunction<S> |
ProbabilitySolver.getProbability() |
ValueFunction<S> |
Solver.getValueFunction()
If the problem is solved, it will return the optimal value function.
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