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Class sim.mdp.Hall

java.lang.Object
   |
   +----sim.mdp.MDP
           |
           +----sim.mdp.Hall

public class Hall
extends MDP
A Markov Chain that takes a state and returns a new state and a reinforcement. If the next state is fed back in as the state, it can run a simulation. If the state is repeatedly randomized, it can be used for learning with random transitions. The chain has boundaries of [-1,1]. The number of states is dependent upon dt. The reinforcement on each transition is 1 and state 1 is an absorbing state with a value of 0.

This code is (c) 1996 Mance E. Harmon <harmonme@aa.wpafb.af.mil>, http://www.aa.wpafb.af.mil/~harmonme
The source and object code may be redistributed freely provided no fee is charged. If the code is modified, please state so in the comments.

Version:
1.06, 17 June 97
Author:
Mance Harmon

Variable Index

 o random
The random number generator

Constructor Index

 o Hall()

Method Index

 o actionSize()
Return the number of elements in the action vector.
 o BNF(int)
Return the BNF description of how to parse the parameters of this object.
 o findValAct(MatrixD, MatrixD, FunApp, MatrixD, PBoolean)
Find the value and best action of this state.
 o findValue(MatrixD, MatrixD, PDouble, FunApp, PDouble, MatrixD, PDouble, PBoolean, NumExp, Random)
Find the max over actions for where V(x') is the value of the successor state given state x, R is the reinforcement, gamma is the discount factor.
 o getAction(MatrixD, MatrixD, Random)
Return the next possible action in a state given an action.
 o getState(MatrixD, PDouble, Random)
Return the next state when doing epoch-wise training.
 o initialAction(MatrixD, MatrixD, Random)
Return an initial action possible in a given state.
 o initialState(MatrixD, Random)
Return a start state for epoch-wise training.
 o nextState(MatrixD, MatrixD, MatrixD, PDouble, PBoolean, Random)
Find the next state given a state and action, and return the reinforcement received.
 o numActions(MatrixD)
Return the number of actions in each state.
 o numPairs(PDouble)
Return the number of state/action pairs for a given dt.
 o numStates(PDouble)
Return the number of states in this LQR for a given dt.
 o parse(Parser, int)
Parse the input file to get the parameters for this object.
 o randomAction(MatrixD, MatrixD, Random)
Generates a random action from those possible.
 o randomState(MatrixD, Random)
Generates a random state from those possible.
 o stateSize()
Return the number of elements in the state vector.
 o unparse(Unparser, int)
Output a description of this object that can be parsed with parse().

Variables

 o random
 protected Random random
The random number generator

Constructors

 o Hall
 public Hall()

Methods

 o numStates
 public int numStates(PDouble dt)
Return the number of states in this LQR for a given dt. The state space is the number line from [-1,1] and is discretized in units of dt.

Overrides:
numStates in class MDP
 o stateSize
 public int stateSize()
Return the number of elements in the state vector.

Overrides:
stateSize in class MDP
 o initialState
 public void initialState(MatrixD state,
                          Random random) throws MatrixException
Return a start state for epoch-wise training.

Throws: MatrixException
Vector is the wrong length.
Overrides:
initialState in class MDP
 o getState
 public void getState(MatrixD state,
                      PDouble dt,
                      Random random) throws MatrixException
Return the next state when doing epoch-wise training. This functions as a circular queue.

Throws: MatrixException
Vector is the wrong length.
Overrides:
getState in class MDP
 o actionSize
 public int actionSize()
Return the number of elements in the action vector.

Overrides:
actionSize in class MDP
 o numActions
 public int numActions(MatrixD state)
Return the number of actions in each state.

Overrides:
numActions in class MDP
 o initialAction
 public void initialAction(MatrixD state,
                           MatrixD action,
                           Random random) throws MatrixException
Return an initial action possible in a given state.

Throws: MatrixException
Vector is the wrong length.
Overrides:
initialAction in class MDP
 o getAction
 public void getAction(MatrixD state,
                       MatrixD action,
                       Random random) throws MatrixException
Return the next possible action in a state given an action.

Throws: MatrixException
Vector is the wrong length.
Overrides:
getAction in class MDP
 o numPairs
 public int numPairs(PDouble dt)
Return the number of state/action pairs for a given dt. This only works for dt's in which 2 is evenly divisible by dt.

Overrides:
numPairs in class MDP
 o randomAction
 public void randomAction(MatrixD state,
                          MatrixD action,
                          Random random) throws MatrixException
Generates a random action from those possible.

Throws: MatrixException
Vector is the wrong length.
Overrides:
randomAction in class MDP
 o randomState
 public void randomState(MatrixD state,
                         Random random) throws MatrixException
Generates a random state from those possible.

Throws: MatrixException
Vector is the wrong length.
Overrides:
randomState in class MDP
 o nextState
 public double nextState(MatrixD state,
                         MatrixD action,
                         MatrixD newState,
                         PDouble dt,
                         PBoolean valueKnown,
                         Random random) throws MatrixException
Find the next state given a state and action, and return the reinforcement received. All 3 should be vectors (single-column matrices). The duration of the time step, dt, is also returned.

Throws: MatrixException
if sizes aren't right.
Overrides:
nextState in class MDP
 o findValAct
 public double findValAct(MatrixD state,
                          MatrixD action,
                          FunApp f,
                          MatrixD outputs,
                          PBoolean valueKnown) throws MatrixException
Find the value and best action of this state.

Throws: MatrixException
column vectors are wrong size or shape
Overrides:
findValAct in class MDP
 o findValue
 public double findValue(MatrixD state,
                         MatrixD action,
                         PDouble gamma,
                         FunApp f,
                         PDouble dt,
                         MatrixD outputs,
                         PDouble reinforcement,
                         PBoolean valueKnown,
                         NumExp explorationFactor,
                         Random random) throws MatrixException
Find the max over actions for where V(x') is the value of the successor state given state x, R is the reinforcement, gamma is the discount factor. Return This method is used in the object ValIteration (value iteration). The last performed in this method should be done for the successor state associate with the optimal action. In this case there is only one action.

Throws: MatrixException
column vectors are wrong size or shape
Overrides:
findValue in class MDP
 o BNF
 public String BNF(int lang)
Return the BNF description of how to parse the parameters of this object.

Overrides:
BNF in class MDP
 o unparse
 public void unparse(Unparser u,
                     int lang)
Output a description of this object that can be parsed with parse().

Overrides:
unparse in class MDP
See Also:
Parsable
 o parse
 public Object parse(Parser p,
                     int lang) throws ParserException
Parse the input file to get the parameters for this object.

Throws: ParserException
parser didn't find the required token
Overrides:
parse in class MDP

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