From e2b05e2cc4e56b407662f19040405e6d974c5b1f Mon Sep 17 00:00:00 2001
From: BrunoDatoMeneses <bruno.dato.meneses@gmail.com>
Date: Mon, 13 Jan 2020 18:27:29 +0100
Subject: [PATCH] ADD: volume for best context selection
---
AMOEBAonAMAK/src/agents/context/Context.java | 12 +-
AMOEBAonAMAK/src/agents/context/Range.java | 53 +++--
AMOEBAonAMAK/src/agents/head/Head.java | 235 ++++++++++---------
AMOEBAonAMAK/src/kernel/World.java | 2 +-
4 files changed, 162 insertions(+), 140 deletions(-)
diff --git a/AMOEBAonAMAK/src/agents/context/Context.java b/AMOEBAonAMAK/src/agents/context/Context.java
index db891d06..7dcef4ea 100644
--- a/AMOEBAonAMAK/src/agents/context/Context.java
+++ b/AMOEBAonAMAK/src/agents/context/Context.java
@@ -119,7 +119,7 @@ public class Context extends AmoebaAgent {
if(getAmas().getHeadAgent().activatedNeighborsContexts.size()>0) {
getAmas().getEnvironment()
.trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("Range creation by mean", this.getName(), p.getName(), getAmas().getHeadAgent().meanNeighborhoodRaduises.get(p).toString())));
- r = new Range(this, p.getValue() - getAmas().getHeadAgent().meanNeighborhoodRaduises.get(p), p.getValue() + getAmas().getHeadAgent().meanNeighborhoodRaduises.get(p), 0, true, true, p, getAmas().getHeadAgent().meanNeighborhoodStartIncrements.get(p), getAmas().getHeadAgent().meanNeighborhoodEndIncrements.get(p));
+ r = new Range(this, p.getValue() - getAmas().getHeadAgent().minMeanNeighborhoodRaduises, p.getValue() + getAmas().getHeadAgent().minMeanNeighborhoodRaduises, 0, true, true, p, getAmas().getHeadAgent().minMeanNeighborhoodStartIncrements, getAmas().getHeadAgent().minMeanNeighborhoodEndIncrements);
}else {
r = new Range(this, p.getValue() - radiuses.getA(), p.getValue() + radiuses.getB(), 0, true, true, p);
getAmas().getEnvironment()
@@ -201,7 +201,7 @@ public class Context extends AmoebaAgent {
if(getAmas().getHeadAgent().activatedNeighborsContexts.size()>0) {
getAmas().getEnvironment()
.trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("Range creation by mean", this.getName(), p.getName(), getAmas().getHeadAgent().meanNeighborhoodRaduises.get(p).toString())));
- r = new Range(this, p.getValue() - getAmas().getHeadAgent().meanNeighborhoodRaduises.get(p), p.getValue() + getAmas().getHeadAgent().meanNeighborhoodRaduises.get(p), 0, true, true, p, getAmas().getHeadAgent().meanNeighborhoodStartIncrements.get(p), getAmas().getHeadAgent().meanNeighborhoodEndIncrements.get(p));
+ r = new Range(this, p.getValue() - getAmas().getHeadAgent().minMeanNeighborhoodRaduises, p.getValue() + getAmas().getHeadAgent().minMeanNeighborhoodRaduises, 0, true, true, p, getAmas().getHeadAgent().minMeanNeighborhoodStartIncrements, getAmas().getHeadAgent().minMeanNeighborhoodEndIncrements);
}else {
r = new Range(this, p.getValue() - radiuses.getA(), p.getValue() + radiuses.getB(), 0, true, true, p);
getAmas().getEnvironment()
@@ -785,7 +785,7 @@ public class Context extends AmoebaAgent {
this.getRanges().get(pct).setStart(Math.min(this.getRanges().get(pct).getStart(), fusionContext.getRanges().get(pct).getStart()));
}
- this.setConfidence(Math.max(this.getConfidence(), fusionContext.getConfidence()));
+ this.setConfidence(2*Math.max(this.getConfidence(), fusionContext.getConfidence()));
regressionPerformance.setPerformanceIndicator(Math.max(this.regressionPerformance.getPerformanceIndicator(), fusionContext.regressionPerformance.getPerformanceIndicator()));
@@ -889,7 +889,7 @@ public class Context extends AmoebaAgent {
// ranges.get(p).adapt(p.getValue());
// }
- ranges.get(p).adapt(p.getValue());
+ ranges.get(p).adapt(p.getValue(), false, null);
// if(perceptForAdapatationAndOverlapingContext.getB()!=null) {
// if(testIfOtherContextShouldFinalyShrink(perceptForAdapatationAndOverlapingContext.getB(), perceptForAdapatationAndOverlapingContext.getA())){
@@ -1220,7 +1220,7 @@ public class Context extends AmoebaAgent {
getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(this.getName(), "CONTAINED", ""+contain)));
if (!contain && !fusionned) {
if(ranges.get(pct).getLenght()<pct.getMappingErrorAllowedMax()) {
- ranges.get(pct).adapt(pct.getValue());
+ ranges.get(pct).adapt(pct.getValue(), false, null);
}
//ranges.get(pct).extend(pct.getValue(), pct);
@@ -1245,7 +1245,7 @@ public class Context extends AmoebaAgent {
} else {
- ranges.get(perceptWithBiggerImpactOnOverlap).adapt(perceptWithBiggerImpactOnOverlap.getValue());
+ ranges.get(perceptWithBiggerImpactOnOverlap).adapt(perceptWithBiggerImpactOnOverlap.getValue(), true, bestContext);
}
}
diff --git a/AMOEBAonAMAK/src/agents/context/Range.java b/AMOEBAonAMAK/src/agents/context/Range.java
index a40fd60b..25ba066f 100644
--- a/AMOEBAonAMAK/src/agents/context/Range.java
+++ b/AMOEBAonAMAK/src/agents/context/Range.java
@@ -217,12 +217,12 @@ public class Range implements Serializable, Comparable, Cloneable {
* @param oracleValue the oracle value
* @param p the p
*/
- public void adapt(Double oracleValue, double increment) {
+ public void adapt(Double oracleValue, double increment, boolean isOverlap, Context bestContext) {
if (!isPerceptEnum()) {
double minIncrement = Math.min(increment, getIncrement());
- staticAdapt(oracleValue, minIncrement);
+ staticAdapt(oracleValue, minIncrement, isOverlap, bestContext);
// adaptUsingAVT(c, oracleValue);
// adaptWithoutAVT(c, oracleValue);
@@ -235,10 +235,10 @@ public class Range implements Serializable, Comparable, Cloneable {
}
}
- public void adapt(Double oracleValue) {
+ public void adapt(Double oracleValue, boolean isOverlap, Context bestContext) {
if (!isPerceptEnum()) {
- staticAdapt(oracleValue, getIncrement());
+ staticAdapt(oracleValue, getIncrement(), isOverlap, bestContext);
// adaptUsingAVT(c, oracleValue);
// adaptWithoutAVT(c, oracleValue);
@@ -250,6 +250,8 @@ public class Range implements Serializable, Comparable, Cloneable {
// }
}
}
+
+
/**
* Adapt without AVT.
@@ -310,11 +312,11 @@ public class Range implements Serializable, Comparable, Cloneable {
}
- private void staticAdapt(double oracleValue, double increment) {
+ private void staticAdapt(double oracleValue, double increment, boolean isOverlap, Context bestContext) {
if (Math.abs(end - oracleValue) < Math.abs(oracleValue - start)) {
- adaptEnd(oracleValue, increment);
+ adaptEnd(oracleValue, increment, isOverlap, bestContext);
} else {
- adaptStart(oracleValue, increment);
+ adaptStart(oracleValue, increment, isOverlap, bestContext);
}
}
@@ -399,15 +401,15 @@ public class Range implements Serializable, Comparable, Cloneable {
}
- private void adaptEnd(double oracleValue, double increment) {
+ private void adaptEnd(double oracleValue, double increment, boolean isOverlap, Context bestContext) {
world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("INCREMENT ON END ADAPT", context.getName(), percept.getName(), "" + increment )));
- classicEndAdapt(oracleValue, increment);
+ classicEndAdapt(oracleValue, increment, isOverlap, bestContext);
// adaptEndWithSplitting(oracleValue, increment);
}
- private void classicEndAdapt(double oracleValue, double increment) {
+ private void classicEndAdapt(double oracleValue, double increment, boolean isOverlap, Context bestContext) {
if (!(contains(oracleValue) == 0.0)) { // value not contained --> end range will grow (growing direction = 1)
if (lastEndDirection == -1) { // opposite direction -> negative feedback
@@ -424,7 +426,10 @@ public class Range implements Serializable, Comparable, Cloneable {
// endIncrement *=2;
}
+
this.setEnd(end + endIncrement);
+
+
} else { // value contained --> end range will shrink (shrinking direction = -1)
if (lastEndDirection == 1) { // opposite direction -> negative feedback
@@ -441,7 +446,12 @@ public class Range implements Serializable, Comparable, Cloneable {
// endIncrement *=2;
}
- this.setEnd(end - endIncrement);
+ if(isOverlap) {
+ this.setEnd(bestContext.getRanges().get(this.percept).getStart());
+ }else {
+ this.setEnd(end - endIncrement);
+ }
+
}
@@ -570,16 +580,16 @@ public class Range implements Serializable, Comparable, Cloneable {
}
- private void adaptStart(double oracleValue, double increment) {
+ private void adaptStart(double oracleValue, double increment, boolean isOverlap, Context bestContext) {
world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("INCREMENT ON END ADAPT", context.getName(), percept.getName(), "" + increment )));
- classicStartAdapt(oracleValue, increment);
+ classicStartAdapt(oracleValue, increment, isOverlap, bestContext);
// adaptStartWithSplitting(oracleValue, increment);
}
- private void classicStartAdapt(double oracleValue, double increment) {
+ private void classicStartAdapt(double oracleValue, double increment, boolean isOverlap, Context bestContext) {
if (!(contains(oracleValue) == 0.0)) {
if (lastStartDirection == -1) {
@@ -635,7 +645,12 @@ public class Range implements Serializable, Comparable, Cloneable {
// startIncrement
// );
- this.setStart(start + startIncrement);
+
+ if(isOverlap) {
+ this.setStart(bestContext.getRanges().get(this.percept).getEnd());
+ }else {
+ this.setStart(start + startIncrement);
+ }
}
// this.setStart(start + getIncrementDependingOnNeighboorDistances("start"));
@@ -1022,16 +1037,16 @@ public class Range implements Serializable, Comparable, Cloneable {
if (overlapDistance(overlappingContextRanges) > nonOverlapDistance(overlappingContextRanges)) {
if (Math.abs(end - border) > Math.abs(border - start)) {
- adaptEnd(border, increment);
+ adaptEnd(border, increment, false, null);
} else {
- adaptStart(border, increment);
+ adaptStart(border, increment, false, null);
}
} else {
if (Math.abs(end - border) < Math.abs(border - start)) {
- adaptEnd(border, increment);
+ adaptEnd(border, increment, false, null);
} else {
- adaptStart(border, increment);
+ adaptStart(border, increment, false, null);
}
}
diff --git a/AMOEBAonAMAK/src/agents/head/Head.java b/AMOEBAonAMAK/src/agents/head/Head.java
index 154f21ab..2a82381f 100644
--- a/AMOEBAonAMAK/src/agents/head/Head.java
+++ b/AMOEBAonAMAK/src/agents/head/Head.java
@@ -47,6 +47,10 @@ public class Head extends AmoebaAgent {
public HashMap<Percept, Double> meanNeighborhoodStartIncrements;
public HashMap<Percept, Double> meanNeighborhoodEndIncrements;
+ public Double minMeanNeighborhoodRaduises = null;
+ public Double minMeanNeighborhoodStartIncrements = null;
+ public Double minMeanNeighborhoodEndIncrements = null;
+
Queue<EndogenousRequest> endogenousRequests = new PriorityQueue<EndogenousRequest>(new Comparator<EndogenousRequest>(){
public int compare(EndogenousRequest r1, EndogenousRequest r2) {
@@ -90,6 +94,10 @@ public class Head extends AmoebaAgent {
meanNeighborhoodEndIncrements = null;
meanNeighborhoodStartIncrements = null;
+ minMeanNeighborhoodRaduises = Double.POSITIVE_INFINITY;
+ minMeanNeighborhoodStartIncrements = Double.POSITIVE_INFINITY;
+ minMeanNeighborhoodEndIncrements = Double.POSITIVE_INFINITY;
+
getAmas().data.currentCriticalityPrediction = 0;
getAmas().data.currentCriticalityMapping = 0;
getAmas().data.currentCriticalityConfidence = 0;
@@ -108,6 +116,97 @@ public class Head extends AmoebaAgent {
/* The head memorize last used context agent */
lastUsedContext = bestContext;
bestContext = null;
+
+ /* Neighbors */
+
+
+ double neighborhoodVolumesSum = 0;
+ HashMap<Percept,Double> neighborhoodRangesSums = new HashMap<Percept,Double>();
+ HashMap<Percept,Double> neighborhoodStartIncrementSums = new HashMap<Percept,Double>();
+ HashMap<Percept,Double> neighborhoodEndIncrementSums = new HashMap<Percept,Double>();
+ for (Percept pct : getAmas().getPercepts()) {
+ neighborhoodRangesSums.put(pct, 0.0);
+ neighborhoodStartIncrementSums.put(pct, 0.0);
+ neighborhoodEndIncrementSums.put(pct, 0.0);
+ }
+
+
+
+ if(activatedNeighborsContexts.size()>0) {
+
+ System.out.println(activatedNeighborsContexts);
+
+ for (Context ctxt : activatedNeighborsContexts) {
+
+ neighborhoodVolumesSum += ctxt.getVolume();
+
+ for (Percept pct : ctxt.getRanges().keySet()) {
+ Double oldRadiusSum = neighborhoodRangesSums.get(pct);
+ Double oldStartIncrSum = neighborhoodStartIncrementSums.get(pct);
+ Double oldEndIncrSum = neighborhoodEndIncrementSums.get(pct);
+ neighborhoodRangesSums.put(pct, oldRadiusSum + ctxt.getRanges().get(pct).getRadius());
+ neighborhoodStartIncrementSums.put(pct, oldStartIncrSum + ctxt.getRanges().get(pct).getStartIncrement());
+ neighborhoodEndIncrementSums.put(pct, oldEndIncrSum + ctxt.getRanges().get(pct).getEndIncrement());
+ }
+
+
+ }
+
+ meanNeighborhoodVolume = neighborhoodVolumesSum / activatedNeighborsContexts.size();
+
+ meanNeighborhoodRaduises = new HashMap<Percept, Double>();
+ meanNeighborhoodStartIncrements = new HashMap<Percept, Double>();
+ meanNeighborhoodEndIncrements = new HashMap<Percept, Double>();
+
+
+ for (Percept pct : getAmas().getPercepts()) {
+
+
+ double meanRadius = neighborhoodRangesSums.get(pct)/activatedNeighborsContexts.size();
+ double meanStartIncrement = neighborhoodStartIncrementSums.get(pct)/activatedNeighborsContexts.size();
+ double meanEndIncrement = neighborhoodEndIncrementSums.get(pct)/activatedNeighborsContexts.size();
+ meanNeighborhoodRaduises.put(pct, meanRadius);
+ meanNeighborhoodStartIncrements.put(pct, meanStartIncrement);
+ meanNeighborhoodEndIncrements.put(pct, meanEndIncrement);
+
+ if(meanRadius < minMeanNeighborhoodRaduises) {
+ minMeanNeighborhoodRaduises = meanRadius;
+ }
+ if(meanStartIncrement < minMeanNeighborhoodStartIncrements) {
+ minMeanNeighborhoodStartIncrements = meanStartIncrement;
+ }
+ if(meanEndIncrement < minMeanNeighborhoodEndIncrements) {
+ minMeanNeighborhoodEndIncrements = meanEndIncrement;
+ }
+
+
+ }
+
+
+
+
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "size", ""+activatedNeighborsContexts.size())));
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodVolume", ""+meanNeighborhoodVolume)));
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodRaduises", ""+meanNeighborhoodRaduises)));
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodStartIncrements", ""+meanNeighborhoodStartIncrements)));
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodEndIncrements", ""+meanNeighborhoodEndIncrements)));
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "minMeanNeighborhoodRaduises", ""+minMeanNeighborhoodRaduises)));
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "minMeanNeighborhoodStartIncrements", ""+minMeanNeighborhoodStartIncrements)));
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "minMeanNeighborhoodEndIncrements", ""+minMeanNeighborhoodEndIncrements)));
+ }
+
+
+
+
+
if (getAmas().data.useOracle) {
playWithOracle();
@@ -128,30 +227,19 @@ public class Head extends AmoebaAgent {
int nb=0;
Double meanNeighborsLastPredictions = null;
- double neighborhoodVolumesSum = 0;
- HashMap<Percept,Double> neighborhoodRangesSums = new HashMap<Percept,Double>();
- HashMap<Percept,Double> neighborhoodStartIncrementSums = new HashMap<Percept,Double>();
- HashMap<Percept,Double> neighborhoodEndIncrementSums = new HashMap<Percept,Double>();
- for (Percept pct : getAmas().getPercepts()) {
- neighborhoodRangesSums.put(pct, 0.0);
- neighborhoodStartIncrementSums.put(pct, 0.0);
- neighborhoodEndIncrementSums.put(pct, 0.0);
- }
+
+
+
ArrayList<Context> usedNeighbors = new ArrayList<Context>();
- if(activatedNeighborsContexts.size()>0) { ////////////// TODO no good version
+ if(activatedNeighborsContexts.size()>0) {
meanNeighborsLastPredictions = 0.0;
for (Context ctxt : activatedNeighborsContexts) {
- neighborhoodVolumesSum += ctxt.getVolume();
- for (Percept pct : ctxt.getRanges().keySet()) {
- neighborhoodRangesSums.put(pct, neighborhoodRangesSums.get(pct) + ctxt.getRanges().get(pct).getRadius());
- neighborhoodStartIncrementSums.put(pct, neighborhoodStartIncrementSums.get(pct) + ctxt.getRanges().get(pct).getStartIncrement());
- neighborhoodEndIncrementSums.put(pct, neighborhoodEndIncrementSums.get(pct) + ctxt.getRanges().get(pct).getEndIncrement());
- }
+
if(ctxt.lastPrediction != null) {
usedNeighbors.add(ctxt);
@@ -165,27 +253,16 @@ public class Head extends AmoebaAgent {
else {
meanNeighborsLastPredictions = null;
}
- meanNeighborhoodVolume = neighborhoodVolumesSum / activatedNeighborsContexts.size();
- meanNeighborhoodRaduises = new HashMap<Percept, Double>();
- for (Percept pct : getAmas().getPercepts()) {
- meanNeighborhoodRaduises.put(pct, neighborhoodRangesSums.get(pct)/activatedNeighborsContexts.size());
- meanNeighborhoodStartIncrements.put(pct, neighborhoodStartIncrementSums.get(pct)/activatedNeighborsContexts.size());
- meanNeighborhoodEndIncrements.put(pct, neighborhoodEndIncrementSums.get(pct)/activatedNeighborsContexts.size());
- }
+
+
+
}
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodVolume", meanNeighborhoodVolume.toString())));
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodRaduises", meanNeighborhoodRaduises.toString())));
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodStartIncrements", meanNeighborhoodStartIncrements.toString())));
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodEndIncrements", meanNeighborhoodEndIncrements.toString())));
+
if(meanNeighborsLastPredictions != null) {
// System.out.println("####################### NEIGHBORS #############################");
@@ -210,78 +287,7 @@ public class Head extends AmoebaAgent {
}
- else {
-
-
- double neighborhoodVolumesSum = 0;
- HashMap<Percept,Double> neighborhoodRangesSums = new HashMap<Percept,Double>();
- HashMap<Percept,Double> neighborhoodStartIncrementSums = new HashMap<Percept,Double>();
- HashMap<Percept,Double> neighborhoodEndIncrementSums = new HashMap<Percept,Double>();
- for (Percept pct : getAmas().getPercepts()) {
- neighborhoodRangesSums.put(pct, 0.0);
- neighborhoodStartIncrementSums.put(pct, 0.0);
- neighborhoodEndIncrementSums.put(pct, 0.0);
- }
-
-
-
- if(activatedNeighborsContexts.size()>0) {
-
- System.out.println(activatedNeighborsContexts);
-
- for (Context ctxt : activatedNeighborsContexts) {
-
- neighborhoodVolumesSum += ctxt.getVolume();
-
- for (Percept pct : ctxt.getRanges().keySet()) {
- Double oldRadiusSum = neighborhoodRangesSums.get(pct);
- Double oldStartIncrSum = neighborhoodStartIncrementSums.get(pct);
- Double oldEndIncrSum = neighborhoodEndIncrementSums.get(pct);
- neighborhoodRangesSums.put(pct, oldRadiusSum + ctxt.getRanges().get(pct).getRadius());
- neighborhoodStartIncrementSums.put(pct, oldStartIncrSum + ctxt.getRanges().get(pct).getStartIncrement());
- neighborhoodEndIncrementSums.put(pct, oldEndIncrSum + ctxt.getRanges().get(pct).getEndIncrement());
- }
-
-
- }
- meanNeighborhoodVolume = neighborhoodVolumesSum / activatedNeighborsContexts.size();
-
- meanNeighborhoodRaduises = new HashMap<Percept, Double>();
- meanNeighborhoodStartIncrements = new HashMap<Percept, Double>();
- meanNeighborhoodEndIncrements = new HashMap<Percept, Double>();
-
-
- for (Percept pct : getAmas().getPercepts()) {
-
-
-
- meanNeighborhoodRaduises.put(pct, neighborhoodRangesSums.get(pct)/activatedNeighborsContexts.size());
- meanNeighborhoodStartIncrements.put(pct, neighborhoodStartIncrementSums.get(pct)/activatedNeighborsContexts.size());
- meanNeighborhoodEndIncrements.put(pct, neighborhoodEndIncrementSums.get(pct)/activatedNeighborsContexts.size());
-
-
- }
-
-
-
-
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "size", ""+activatedNeighborsContexts.size())));
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodVolume", ""+meanNeighborhoodVolume)));
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodRaduises", ""+meanNeighborhoodRaduises)));
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodStartIncrements", ""+meanNeighborhoodStartIncrements)));
- getAmas().getEnvironment()
- .trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("NEIGHBORDBOOD", "meanNeighborhoodEndIncrements", ""+meanNeighborhoodEndIncrements)));
- }
-
-
-
-
- }
@@ -295,9 +301,9 @@ public class Head extends AmoebaAgent {
+ "---------------------------------------- PLAY WITH ORACLE")));
if (activatedContexts.size() > 0) {
- //selectBestContext(); // using highest confidence
- selectBestContextWithDistanceToModel(); // using closest distance
- // selectBestContextWithDistanceToModel();
+ //selectBestContextWithConfidenceAndVolume(); // using highest confidence and volume
+ selectBestContextWithDistanceToModelAndVolume(); // using closest distance and volume
+
} else {
bestContext = lastUsedContext;
}
@@ -494,7 +500,7 @@ public class Head extends AmoebaAgent {
logger().debug("HEAD without oracle", "Nombre de contextes activés: " + activatedContexts.size());
- selectBestContext();
+ selectBestContextWithConfidenceAndVolume();
if (bestContext != null) {
getAmas().data.noBestContext = false;
getAmas().data.prediction = bestContext.getActionProposal();
@@ -1536,7 +1542,7 @@ public class Head extends AmoebaAgent {
/**
* Select best context.
*/
- private void selectBestContext() {
+ private void selectBestContextWithConfidenceAndVolume() {
if(activatedContexts != null && !activatedContexts.isEmpty()) {
Context bc;
@@ -1544,9 +1550,10 @@ public class Head extends AmoebaAgent {
double currentConfidence = bc.getConfidence();
for (Context context : activatedContexts) {
- if (context.getConfidence() > currentConfidence) {
+ double confidenceWithVolume = context.getConfidence()*context.getVolume();
+ if (confidenceWithVolume > currentConfidence) {
bc = context;
- currentConfidence = bc.getConfidence();
+ currentConfidence = confidenceWithVolume;
}
}
bestContext = bc;
@@ -1557,20 +1564,20 @@ public class Head extends AmoebaAgent {
- private void selectBestContextWithDistanceToModel() {
+ private void selectBestContextWithDistanceToModelAndVolume() {
Context bc;
bc = activatedContexts.get(0);
double distanceToModel = bc.getLocalModel().distance(bc.getCurrentExperiment());
- double currentDistanceToModel;
+ double currentDistanceToModelWithVolume;
for (Context context : activatedContexts) {
- currentDistanceToModel = context.getLocalModel().distance(context.getCurrentExperiment());
- if (currentDistanceToModel < distanceToModel) {
+ currentDistanceToModelWithVolume = context.getLocalModel().distance(context.getCurrentExperiment())/context.getVolume();
+ if (currentDistanceToModelWithVolume < distanceToModel) {
bc = context;
- distanceToModel = currentDistanceToModel;
+ distanceToModel = currentDistanceToModelWithVolume;
}
}
bestContext = bc;
diff --git a/AMOEBAonAMAK/src/kernel/World.java b/AMOEBAonAMAK/src/kernel/World.java
index c065a4d4..5fe709fe 100644
--- a/AMOEBAonAMAK/src/kernel/World.java
+++ b/AMOEBAonAMAK/src/kernel/World.java
@@ -34,7 +34,7 @@ public class World extends Environment {
- public static TRACE_LEVEL minLevel = TRACE_LEVEL.INFORM;
+ public static TRACE_LEVEL minLevel = TRACE_LEVEL.DEBUG;
private AMOEBA amoeba;
--
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