LearningAgentToSGAgentInterface

java.lang.Object
- burlap.oomdp.stochasticgames.SGAgent
- - burlap.behavior.stochasticgames.agents.interfacing.singleagent.LearningAgentToSGAgentInterface

All Implemented Interfaces:

Environment
```
public class LearningAgentToSGAgentInterface
extends SGAgent
implements Environment
```
A stochastic games SGAgent that takes as input a single agent LearningAgent to handle behavior. The interface from the single agent paradigm to the multi-agent paradigm is handled by this class also implementing the Environment interface. When a game starts, a new thread is launched in which the provided LearningAgent interacts with this class's Environment methods.

When constructing a LearningAgent to use with this class, you should set its Domain to null. Then, when this class joins a world through the joinWorld(burlap.oomdp.stochasticgames.World, burlap.oomdp.stochasticgames.SGAgentType) method, it will automatically use the SGToSADomain to create a SADomain and will then set then LearningAgent to use it.

Author:

James MacGlashan.

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`protected static class`	`LearningAgentToSGAgentInterface.ActionReference` A wrapper that maintains a reference to a `GroundedSGAgentAction` or null.
`protected static class`	`LearningAgentToSGAgentInterface.StateReference` A wrapper that maintains a reference to a `State` or null.

Field Summary

Fields
Modifier and Type	Field and Description
`protected State`	`currentState` The current state of the world
`protected boolean`	`curStateIsTerminal` Whether the last state was a terminal state
`protected double`	`lastReward` The last reward received by this agent
`protected LearningAgent`	`learningAgent` The single agent `LearningAgent` that will be learning in this stochastic game as if the other players are part of the environment.
`protected LearningAgentToSGAgentInterface.ActionReference`	`nextAction` The next action selected by the single agent
`protected LearningAgentToSGAgentInterface.StateReference`	`nextState` The next state received
`protected java.lang.Thread`	`saThread` The thread that runs the single agent learning algorithm

Fields inherited from class burlap.oomdp.stochasticgames.SGAgent
agentType, domain, internalRewardFunction, world, worldAgentName

Constructor Summary

Constructors
Constructor and Description

LearningAgentToSGAgentInterface(SGDomain domain, LearningAgent learningAgent)
Initializes.

Constructors
Constructor and Description
`LearningAgentToSGAgentInterface(SGDomain domain, LearningAgent learningAgent)` Initializes.

Method Summary

Methods
Modifier and Type	Method and Description
`EnvironmentOutcome`	`executeAction(GroundedAction ga)` Executes the specified action in this environment
`void`	`gameStarting()` This method is called by the world when a new game is starting.
`void`	`gameTerminated()` This method is called by the world when a game has ended.
`GroundedSGAgentAction`	`getAction(State s)` This method is called by the world when it needs the agent to choose an action
`State`	`getCurrentObservation()` Returns the current observation of the environment as a `State`.
`double`	`getLastReward()` Returns the last reward returned by the environment
`boolean`	`isInTerminalState()` Returns whether the environment is in a terminal state that prevents further action by the agent.
`void`	`joinWorld(World w, SGAgentType as)` Causes this agent instance to join a world.
`void`	`observeOutcome(State s, JointAction jointAction, java.util.Map<java.lang.String,java.lang.Double> jointReward, State sprime, boolean isTerminal)` This method is called by the world when every agent in the world has taken their action.
`void`	`resetEnvironment()` Resets this environment to some initial state, if the functionality exists.

Methods inherited from class burlap.oomdp.stochasticgames.SGAgent
getAgentName, getAgentType, getInternalRewardFunction, init, setInternalRewardFunction

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - learningAgent
```
protected LearningAgent learningAgent
```
    The single agent LearningAgent that will be learning in this stochastic game as if the other players are part of the environment.
  - curStateIsTerminal
```
protected boolean curStateIsTerminal
```
    Whether the last state was a terminal state
  - lastReward
```
protected double lastReward
```
    The last reward received by this agent
  - currentState
```
protected State currentState
```
    The current state of the world
  - saThread
```
protected java.lang.Thread saThread
```
    The thread that runs the single agent learning algorithm
  - nextAction
```
protected LearningAgentToSGAgentInterface.ActionReference nextAction
```
    The next action selected by the single agent
  - nextState
```
protected LearningAgentToSGAgentInterface.StateReference nextState
```
    The next state received
- Constructor Detail
  - LearningAgentToSGAgentInterface
```
public LearningAgentToSGAgentInterface(SGDomain domain,
                               LearningAgent learningAgent)
```
    Initializes.
    
    Parameters:
    domain - The stochastic games SGDomain in which this agent will interact.
    learningAgent - the LearningAgent that will handle this SGAgent's control.
- Method Detail
  - joinWorld
```
public void joinWorld(World w,
             SGAgentType as)
```
    Description copied from class: SGAgent
    
    Causes this agent instance to join a world.
    
    Overrides:
    
    joinWorld in class SGAgent
    
    Parameters:
    w - the world for the agent to join
    as - the agent type the agent will be joining as
  - gameStarting
```
public void gameStarting()
```
    Description copied from class: SGAgent
    
    This method is called by the world when a new game is starting.
    
    Specified by:
    
    gameStarting in class SGAgent
  - getAction
```
public GroundedSGAgentAction getAction(State s)
```
    Description copied from class: SGAgent
    
    This method is called by the world when it needs the agent to choose an action
    
    Specified by:
    
    getAction in class SGAgent
    
    Parameters:
    s - the current state of the world
    
    Returns:
    the action this agent wishes to take
  - observeOutcome
```
public void observeOutcome(State s,
                  JointAction jointAction,
                  java.util.Map<java.lang.String,java.lang.Double> jointReward,
                  State sprime,
                  boolean isTerminal)
```
    Description copied from class: SGAgent
    
    This method is called by the world when every agent in the world has taken their action. It conveys the result of the joint action.
    
    Specified by:
    
    observeOutcome in class SGAgent
    
    Parameters:
    s - the state in which the last action of each agent was taken
    jointAction - the joint action of all agents in the world
    jointReward - the joint reward of all agents in the world
    sprime - the next state to which the agent transitioned
    isTerminal - whether the new state is a terminal state
  - gameTerminated
```
public void gameTerminated()
```
    Description copied from class: SGAgent
    
    This method is called by the world when a game has ended.
    
    Specified by:
    
    gameTerminated in class SGAgent
  - getCurrentObservation
```
public State getCurrentObservation()
```
    Description copied from interface: Environment
    
    Returns the current observation of the environment as a State.
    
    Specified by:
    
    getCurrentObservation in interface Environment
    
    Returns:
    the current observation of the environment as a State.
  - executeAction
```
public EnvironmentOutcome executeAction(GroundedAction ga)
```
    Description copied from interface: Environment
    
    Executes the specified action in this environment
    
    Specified by:
    
    executeAction in interface Environment
    
    Parameters:
    ga - the GroundedAction that is to be performed in this environment.
    
    Returns:
    the resulting observation and reward transition from applying the given GroundedAction in this environment.
  - getLastReward
```
public double getLastReward()
```
    Description copied from interface: Environment
    
    Returns the last reward returned by the environment
    
    Specified by:
    
    getLastReward in interface Environment
    
    Returns:
    the last reward returned by the environment
  - isInTerminalState
```
public boolean isInTerminalState()
```
    Description copied from interface: Environment
    
    Returns whether the environment is in a terminal state that prevents further action by the agent.
    
    Specified by:
    
    isInTerminalState in interface Environment
    
    Returns:
    true if the current environment is in a terminal state; false otherwise.
  - resetEnvironment
```
public void resetEnvironment()
```
    Description copied from interface: Environment
    
    Resets this environment to some initial state, if the functionality exists.
    
    Specified by:
    
    resetEnvironment in interface Environment

Class LearningAgentToSGAgentInterface

Nested Class Summary

Field Summary

Fields inherited from class burlap.oomdp.stochasticgames.SGAgent

Constructor Summary

Method Summary

Methods inherited from class burlap.oomdp.stochasticgames.SGAgent

Methods inherited from class java.lang.Object

Field Detail

learningAgent

curStateIsTerminal

lastReward

currentState

saThread

nextAction

nextState

Constructor Detail

LearningAgentToSGAgentInterface

Method Detail

joinWorld

gameStarting

getAction

observeOutcome

gameTerminated

getCurrentObservation

executeAction

getLastReward

isInTerminalState

resetEnvironment