v0.0.2

conf/epos.properties

@@ -1,125 +1,95 @@
 ### Dataset ###
-#The folder name in the datasets path. 
-#Make sure it has no spaces, tabs or newlines 
-#(alphanum and underscore combination preferred)
-dataset=gaussian 				
+#The folder name in the datasets path. Make sure it has no spaces, tabs or newlines (alphanum and underscore preferred)
+dataset=gaussian
 
 
-### Basic epos parameters ###
-# number of simulations for whole epos experiments
+### Basic epos properties ###
 # any integer > 0
 numSimulations=5
 
-# maximum number of iterations per simulation
 # any integer > 0
 numIterations=40
 
-# number of children per node in the EPOS
-# tree. The tree is always symmetric and balanced
 # any integer > 0
-numChildren=2
+numAgents=100
 
-# number of agent used for the experiment
-# if it is higher than available agents in
-# dataset, the maximum available agents will
-# be used.
 # any integer > 0
-numAgents=1000
+numPlans=10
 
-# number of plans used per agent
-# if it is higher than the available plans
-# per agent, the maximum number will be used
 # any integer > 0
-numPlans=500
+numChildren=2
 
-# number of plan dimensions used from the start
-# of the plan. if more than available, the maximum
-# available are used.
-# any integer > 0
+# exact dimensionality from the dataset
 planDim=100
 
 
 ### Shuffle seeds ###
 
-# initial agent structure before reorganization occurs
-# any integer > 0
+# initial agent structure before reorganization occurs, any integer > 0
 shuffle=0
 
-# path to a file containing permutation of indices
-# file structure: one column integer index in each row
+# path to a file containing permutation of indices, need its strucure: sphinx one column: integer index in each row
 shuffle_file="permutation.csv" 
 
-
 ### Weights of the global complex cost ###
+numberOfWeights = 2
+weightsString = "0.0,0.0"
+# number of weights used in EPOS cost function
+# weights are in string format, separated by ","
 
+# weight1: in multiobjective EPOS, this is alpha (in this example 0.2)
 # double from [0, 1], alpha + beta <= 1, unfairness
-alpha=0.2
-
+# weight2 in in multiobjective EPOS, this is beta (in this example 0.0)
 # double from [0, 1], alpha + beta <= 1, local objective
-beta=0
-
-# alpha*unfairness + beta*local_cost + (1-alpha-beta)*global_costs
-
-
-### Cost Functions ###
-
-# Available cost function choices:
-# NoGoal "MAX":max value,  "VAR":variance, "STD":standard deviation,
-# "INDEX": plan index value, "PREF": preference, "DISC": discomfort
-# Goal Singal "SQR":square distance, "RMSE":root mean squared error, 
-# "RSS":residual sum of squares, "DOT":dot product, "XCORR":cross correlation
-
-# Suggested values : "XCORR", VAR", "RSS", "RMSE"
-globalCostFunction="VAR"
-
-# Suggested values : "INDEX"  "DISC", "PREF"
-localCostFunction="INDEX"  
-
-# "MIN-MAX", "STD", "UNIT-LENGTH", only for "RSS" cost
-scaling="MIN-MAX"
-
-
-### Goal Signal ###
-
-# filepath of the file containing the vector to be used as goal signal
-# goal signal dimension are expected to be same as planDim,
-# otherwise cropping or repetitive padding might occur
-# if no path is provided, it will search for a “.target” file in the dataset folder
-# if no file is found at all a zero valued goal signal will be generated
-goalSignalPath=default
+#a*unfairness + b*local_cost + (1-a-b)*global_costs
+#avg local cost is local cost
 
 
 
 ### Reorganization strategy ###
 
-# possible values: periodically, convergence, globalCostReduction, never. 
-strategy=periodically
+# possible values: periodically, convergence, globalCostReduction, never. never_strategy: never does reorganization
+strategy=never
 
 # any integer > 0, if "periodically" strategy is chosen
 periodically.reorganizationPeriod=3
 
-# any positive integer > 0, if convergence strategy is chosen
+# any positive integer (>0), if "convergence" strategy is chosen, the iteration at which the selections will be memorized to be sued after the following reorganization
 convergence.memorizationOffset=5
 
 # double from [0, 1]
 globalCost.reductionThreshold=0.5
 
-# any integer, keep same for reproducibility
+# any integer. Keep the same seed to reproduce experiment results, what random permutations each strategy will explore, result reproducability
 strategy.reorganizationSeed=0
 
+
+
+#sphinx
+goalSignalPath=default
+#vector target for global response same dimensionality as plan
+#filepath
+globalCostFunction=VAR
+# "VAR", "RSS", "RMSE", goal signal is ignored in funcitons with only global response as input, e.g. var
+scaling="MIN-MAX"
+# "STD", "UNIT-LENGTH", only for rss, 
+localCostFunction="INDEX"  
+# "COST", "PREF", # cost changes to discomfort
+
+
 ### Loggers ###
-logger.GlobalCostLogger=true
-logger.LocalCostMultiObjectiveLogger=true
-logger.TerminationLogger=true
-logger.SelectedPlanLogger=true
-logger.GlobalResponseVectorLogger=true
-logger.PlanFrequencyLogger=true
-logger.UnfairnessLogger=true
-logger.GlobalComplexCostLogger=true
-logger.WeightsLogger=true
-logger.ReorganizationLogger=true
-
-# Code related logger for debugging and checks please check here:
-# https://docs.oracle.com/javase/7/docs/api/java/util/logging/Level.html. 
-# For experiments "SEVERE" is preferred 
+logger.GlobalCostLogger = true
+logger.LocalCostMultiObjectiveLogger = true
+logger.TerminationLogger = true
+logger.SelectedPlanLogger = true
+logger.GlobalResponseVectorLogger = true
+logger.PlanFrequencyLogger = true
+logger.UnfairnessLogger = true
+logger.GlobalComplexCostLogger = true
+logger.WeightsLogger = true
+logger.ReorganizationLogger = true
+logger.VisualizerLogger = true
+
+#Code related logger for debugging and checks
+# please check here https://docs.oracle.com/javase/7/docs/api/java/util/logging/Level.html. For experiments "SEVERE" is preferred 
 logLevel="SEVERE"

pom.xml

@@ -209,7 +209,7 @@
 								<!-- add Main-Class to manifest file -->
 								<transformer
 									implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
-									<mainClass>experiment.ReorganizationExperiment</mainClass>
+									<mainClass>experiment.IEPOSExperiment</mainClass>
 								</transformer>
 							</transformers>
 						</configuration>

src/main/java/META-INF/MANIFEST.MF

@@ -0,0 +1,3 @@
+Manifest-Version: 1.0
+Main-Class: experiment.IEPOSExperiment
+

src/main/java/agent/MultiObjectiveIEPOSAgent.java

@@ -345,7 +345,6 @@ void processDownMessageMore(DownMessage parentMsg) { }
 
     private void aggregateExtended() {
 //    	System.out.println("EXTENDED!");
-
         if (this.isIterationAfterReorganization()) {
             for (int i = 0; i < this.children.size(); i++) {
                 approvals.add(true);

src/main/java/agent/dataset/DatasetShuffler.java

@@ -25,7 +25,6 @@
 public class DatasetShuffler {
 
 	public static int row = -1;
-	public static Logger log = Logger.getLogger(DatasetShuffler.class.getName());
 
 	/**
 	 * Default mapping is 0->0, 1->1, 2->2, ..
@@ -62,8 +61,8 @@ public static Map<Integer, Integer> getMappingByShuffling(Configuration config)
 
 		long timeAfter = System.currentTimeMillis();
 
-		log.info("Permuting time: " + ((timeAfter-timeBefore)/1000) + " seconds.");		
-		log.info(Configuration.mapping.toString());
+		System.out.println("Permuting time: " + ((timeAfter-timeBefore)/1000) + " seconds.");		
+		System.out.println(Configuration.mapping.toString());
 
 		return Configuration.mapping;
 	}
@@ -81,7 +80,7 @@ public static Map<Integer, Integer> getMappingForRepetitiveExperiments(Configura
 
 		long timeAfter = System.currentTimeMillis();
 
-		log.info("Permuting time: " + ((timeAfter-timeBefore)/1000) + " seconds.");
+		System.out.println("Permuting time: " + ((timeAfter-timeBefore)/1000) + " seconds.");
 
 		return Configuration.mapping;
 	}
@@ -131,7 +130,7 @@ public static Map<Integer, Integer> getMappingFromFile() {
 			Logger.getLogger(DatasetShuffler.class.getName()).log(Level.SEVERE, null, e);
 		}
 
-		//System.out.println(mapping.toString());		
+		System.out.println(mapping.toString());		
 		return mapping;
 	}
 

src/main/java/agent/logging/PlanFrequencyLogger.java

@@ -89,7 +89,7 @@ private String internalFetching(MeasurementLog log) {
 		allTokens.addAll(log.getTagsOfType(Token.class));
 		Iterator<Object> iter = allTokens.iterator();
 
-		//System.out.println("Size is: " + allTokens.size());
+//		System.out.println("Size is: " + allTokens.size());
 
 		HashMap<Integer, HashMap<Integer, ArrayList<Token>>> perRun = 
 				new HashMap<Integer, HashMap<Integer, ArrayList<Token>>>();    // <run, <idx, list>>