public override bool init(AGameGraph G, IGameParams prm, IPolicyGUIInputProvider gui, Dictionary <string, string> policyInput)
{
this.g = (GridGameGraph)G;
this.gm = (GoEGameParams )prm;
this.pgui = gui;
foreach (Pursuer p in gm.A_P)
{
currentPursuersLocations[p] = new Location(Location.Type.Unset);
}
return(true);
}
/// <summary>
///
/// </summary>
/// <param name="ep"></param>
/// <param name="pp"></param>
/// <param name="gameGraph"></param>
/// <param name="input">
/// includes policies input + optimizer specific parameters
/// </param>
/// <paparam name="log">
/// slow optimizers may report progress using this log, each line will have 'LogID' appended
/// </paparam>
public void init(AGameGraph GameGraph,
IGameParams GameParams,
Dictionary <string, string> input)
{
policyInput = new Dictionary <string, string>(input);
gameGraph = GameGraph;
igameParams = GameParams;
repetitionCount =
int.Parse(GoE.AppConstants.Algorithms.Optimizers.REPETITION_COUNT_KEY.tryRead(policyInput));
initEx();
}
public static APolicyOptimizer getOptimizedPolicyInput(ParallelOptions parallelOptInner,
Dictionary <string, string> processArgs,
AGameGraph graph,
AGameProcess game,
IGameParams gameParams)
{
// use optimizer, if specified
string optimizerName = AppConstants.AppArgumentKeys.POLICY_OPTIMIZER.tryRead(processArgs);
if (optimizerName == "")
{
return(null);
}
Type policyOptimizerType = APolicyOptimizer.ChildrenByTypename[optimizerName];
//AppSettings.WriteLogLine("invoking optimizer ...");
APolicyOptimizer opt = (APolicyOptimizer)policyOptimizerType.GetConstructor(new Type[] { }).Invoke(new object[] { });
opt.init(graph, gameParams, processArgs);
opt.process(parallelOptInner);
return(opt);
}
public override bool init(AGameGraph G, IGameParams prm, IPolicyGUIInputProvider pgui, Dictionary <string, string> policyParams)
{
IntrusionGameParams concreateParam = (IntrusionGameParams)prm;
return(init(G, concreateParam, pgui, policyParams));
}
public void initParams(IGameParams param, AGameGraph GameGraph)
{
graph = (EmptyEnvironment)GameGraph;
this.Params = (AdvRoutingGameParams)param;
}
public bool init(AGameGraph G, IGameParams prm, APursuersPolicy initializedPursuers, IPolicyGUIInputProvider pgui, Dictionary <string, string> policyParams = null)
{
return(init(G, (IntrusionGameParams)prm, initializedPursuers, pgui, policyParams));
}
/// <summary>
/// called once after object is constructed
/// </summary>
/// <param name="G"></param>
/// <param name="prm"></param>
/// <param name="pgui"></param>
/// <param name="PreprocessResult">
/// expected to include results from preProcess(), or from some other source (with the same keys e.g. a compatible optimizer)
/// </param>
/// <returns>
/// false if game parameters don't allow using this policy
/// </returns>
public abstract bool init(AGameGraph G, IGameParams prm, IPolicyGUIInputProvider pgui,
Dictionary <string, string> policyParams);
/// <summary>
/// assumes 'processArgs' had a specific optimizer and/or policies, and uses them for the process
/// </summary>
/// <param name="parallelOptInner"></param>
/// <param name="initialProcessArgs">
/// empty values (i.e. keys with empty strings) will be ignored
/// </param>
/// <param name="graph"></param>
/// <param name="optimizeInitialProcessArgs">
/// if false, theoryOutput and optimizerOutput will not be populated
/// and no optimizer will be used to override any of the values in optimizeInitialProcessArgs
/// </param>
/// <returns></returns>
public static ProcessOutput processParams(ParallelOptions parallelOptInner,
Dictionary <string, string> initialProcessArgs,
AGameGraph graph,
bool optimizeInitialProcessArgs = true,
bool calcStdDev = true)
{
ProcessOutput res = new ProcessOutput();
var processArgs = new Dictionary <string, string>(initialProcessArgs);
foreach (var val in initialProcessArgs)
{
if (val.Value == "")
{
processArgs.Remove(val.Key);
}
}
// allocate game process
string gameType = AppConstants.AppArgumentKeys.GAME_MODEL.tryRead(processArgs);
AGameProcess game = Utils.ReflectionUtils.constructEmptyCtorType <AGameProcess>(gameType);
// load game params file. processArgs may override some of the loaded values
IGameParams gameParams = game.constructGameParams();
gameParams.deserialize(AppConstants.AppArgumentKeys.PARAM_FILE_PATH.tryRead(processArgs), processArgs);
APolicyOptimizer preferredOptimizer = null;// null if no optimizer specified
if (optimizeInitialProcessArgs)
{
preferredOptimizer = getOptimizedPolicyInput(parallelOptInner, processArgs, graph, game, gameParams);
}
// if an optimizer was specified, it may have the freedom to choose from several policies, and also provide theoretical bounds *given this freedom*
// note that the optimizer may attempt choosing policies, but can't override values in init file.
string evadersPolicy, pursuersPolicy;
if (preferredOptimizer != null)
{
res.theoryOutput = new Dictionary <string, string>(processArgs);
// FIXME: for creating theoryOutput, if pursuers policy wasn't specificed in input params, we throw an exception.
// this is not necessarily the correct way to do this, since theoretically the optimizer is the one that decides what pursuers policy
// to use
res.theoryOutput.AddRange(getPursuersPolicyTheoreticalOptimizerResult(AppConstants.AppArgumentKeys.PURSUER_POLICY.tryRead(processArgs, ""), graph, gameParams, processArgs));
processArgs.AddRange(preferredOptimizer.optimizationOutput, false);
res.optimizerOutput = new Dictionary <string, string>(processArgs);
res.optimizerOutput.AddRange(preferredOptimizer.optimizationOutput);
}
// evadersPolicy and pursuersPolicy are extracted after the optimizer is used, since the optimizer may choose them
evadersPolicy = AppConstants.AppArgumentKeys.EVADER_POLICY.tryRead(processArgs);
pursuersPolicy = AppConstants.AppArgumentKeys.PURSUER_POLICY.tryRead(processArgs);
// if no optimizer specified, the theoretical results are calculated by the estimator (which assumes specific evaders policy and pursuers policy are given in processArgs)
// similarly to the optimizer, the pursuer's policy can't override previous data in processArgs
if (preferredOptimizer == null && optimizeInitialProcessArgs)
{
res.theoryOutput = new Dictionary <string, string>(processArgs);
var theoreticalOptimizerRes = getPursuersPolicyTheoreticalOptimizerResult(pursuersPolicy, graph, gameParams, processArgs);
res.theoryOutput.AddRange(theoreticalOptimizerRes);
processArgs.AddRange(theoreticalOptimizerRes, false);
}
res.processOutput =
getEstimatedResultsAverage(parallelOptInner, evadersPolicy, pursuersPolicy, gameParams, graph, processArgs, game, calcStdDev);
return(res);
}
/// <summary>
/// constructs pursuers policy object, and returns its theoretical optimizer's output
/// </summary>
/// <param name="pursuersPolicy"></param>
/// <param name="graph"></param>
/// <param name="gameParams"></param>
/// <param name="processArgs"></param>
/// <returns></returns>
public static Dictionary <string, string> getPursuersPolicyTheoreticalOptimizerResult(string pursuersPolicy,
AGameGraph graph,
IGameParams gameParams,
Dictionary <string, string> processArgs)
{
// construct a dummy policy, just to make the one-time calculation of preprocess
APursuersPolicy initPP = ReflectionUtils.constructEmptyCtorType <APursuersPolicy>(pursuersPolicy);
var theoryOptimizer = initPP.constructTheoreticalOptimizer();
if (theoryOptimizer == null)
{
return(new Dictionary <string, string>());
}
theoryOptimizer.init(graph, gameParams, processArgs);
theoryOptimizer.process();
return(theoryOptimizer.optimizationOutput);
}
//public GameProcess(GameParams param, GameGraph<Point> GameGraph)
public void initParams(IGameParams param, AGameGraph GameGraph)
{
this.gr = (GameGraph <Point>)GameGraph;
this.gm = (GoEGameParams)param;
}
