diff --git a/ant/Ant.java b/ant/Ant.java
index 27643bb9e7879bb1694d3f3a886112df8faf5cb2..ef4a793a794d14d980bd231cafcfcc5730bffc41 100644
--- a/ant/Ant.java
+++ b/ant/Ant.java
@@ -4,19 +4,14 @@ import java.util.ArrayList;
import java.util.List;
import java.util.Random;
+import baseOptiAgent.BaseAgent;
import eval.Eval;
-import mas.core.Agent;
-public class Ant extends Agent{
-
- private List<Double> vector;
- double evaluate;
+public class Ant extends BaseAgent{
- Eval eval;
- Env env;
+ AntEnv env;
Phase phase;
- int id;
private double evaporationRate;
@@ -26,7 +21,7 @@ public class Ant extends Agent{
private List<Solution> archive;
private List<Double> archiveProba;
- public Ant(int _id, Eval _eval, Env _env, double _evaporationRate) {
+ public Ant(int _id, Eval _eval, AntEnv _env, double _evaporationRate) {
eval = _eval;
env = _env;
@@ -45,10 +40,6 @@ public class Ant extends Agent{
}
- private double evaluate(List<Double> values) {
- return eval.evaluate(values);
- }
-
private void nextPhase() {
if (phase == Phase.EVALUATE) {
phase = Phase.BUILD_NEW;
@@ -76,9 +67,6 @@ public class Ant extends Agent{
else if (phase == Phase.BUILD_NEW) {
archive = env.getArchive();
archiveProba = env.getArchiveProba();
- if (id == 0) {
- System.out.println(archive);
- }
}
}
@@ -146,14 +134,6 @@ public class Ant extends Agent{
return sol;
}
- public List<Double> getVector() {
- return vector;
- }
-
- public double getEvaluate() {
- return evaluate;
- }
-
public Phase getPhase() {
return phase;
}
diff --git a/ant/Env.java b/ant/AntEnv.java
similarity index 88%
rename from ant/Env.java
rename to ant/AntEnv.java
index 4c7a7f3ec42269d83ffc0e7104ba6773a0acf069..0db7d3c43596d2a3797ed4200784fae3abfaa672 100644
--- a/ant/Env.java
+++ b/ant/AntEnv.java
@@ -6,9 +6,10 @@ import java.util.Comparator;
import java.util.List;
import java.util.Random;
+import baseOptiAgent.Env;
import eval.Eval;
-public class Env {
+public class AntEnv extends Env{
private List<Solution> archive;
private List<Double> archiveProba;
@@ -20,7 +21,7 @@ public class Env {
private int archiveLen;
private double q;
- public Env(int _archiveLen, double _q, Eval _eval) {
+ public AntEnv(int _archiveLen, double _q, Eval _eval) {
archiveLen = _archiveLen;
q = _q;
@@ -99,8 +100,15 @@ public class Env {
public List<Ant> getAgents() {
return agents;
}
-
- public double bestValue() {
+
+ @Override
+ public double getBestFitness() {
+ // TODO Auto-generated method stub
+ return 0;
+ }
+
+ @Override
+ public double getBestEval() {
return archive.get(archive.size()-1).getEval();
}
}
diff --git a/ant/AntSolver.java b/ant/AntSolver.java
new file mode 100644
index 0000000000000000000000000000000000000000..53e9c89252a6d12e96040e1e6d91830de766d8db
--- /dev/null
+++ b/ant/AntSolver.java
@@ -0,0 +1,40 @@
+package ant;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import baseOptiAgent.Result;
+import baseOptiAgent.Solver;
+import eval.Eval;
+
+public class AntSolver extends Solver{
+
+ public AntSolver(Eval _eval, int _maxCycle, int _maxEval) {
+ super(_eval, _maxCycle, _maxEval);
+ name = "Ant";
+ }
+
+ @Override
+ public Result solve() {
+
+ // [PARAM]
+ int nbrAgent = 40;
+ int archiveSize = 10;
+
+ double evaporation = 0.6;
+ double q = 0.2;
+
+ // [INIT]
+ AntEnv env = new AntEnv(archiveSize, q, eval);
+
+ List<Ant> agents = new ArrayList<Ant>();
+ for (int i_agent = 0; i_agent < nbrAgent; i_agent++) {
+ agents.add(new Ant(i_agent, eval, env, evaporation));
+ }
+
+ env.initAgents(agents);
+
+ return findSolution(agents, env, 2);
+ }
+
+}
\ No newline at end of file
diff --git a/ant/MainAnt.java b/ant/MainAnt.java
deleted file mode 100644
index ced49a521384a107f237205a228913ed2e8aef25..0000000000000000000000000000000000000000
--- a/ant/MainAnt.java
+++ /dev/null
@@ -1,119 +0,0 @@
-package ant;
-
-import java.io.IOException;
-import java.util.ArrayList;
-import java.util.List;
-
-import eval.Eval;
-import eval.fun.SchwefelFunction;
-import eval.fun.SchwefelFunction1_2;
-import eval.fun.StepFunction;
-
-/*
- * https://www.sciencedirect.com/science/article/pii/S0952197619301940#fig1
- * https://towardsdatascience.com/introduction-to-global-optimization-algorithms-for-continuous-domain-functions-7ad9d01db055
- */
-
-public class MainAnt {
- public static void main(String[] args) {
- // [PARAM]
-
- int nbrAgent = 40;
- int archiveSize = 10;
-
- double evaporation = 0.6;
- double q = 0.2;
-
- int res = 0;
- int nbrTry = 1;
-
- long startTime = System.currentTimeMillis();
- for (int i = 0; i < nbrTry; i++) {
- // [INIT]
- //Eval eval = new StepFunction();
- Eval eval = new SchwefelFunction1_2();
- //Eval eval = new SchwefelFunction();
- //Eval eval = new Rastrigin();
-
-
- Env env = new Env(archiveSize, q, eval);
-
- List<Ant> agents = new ArrayList<Ant>();
- for (int i_agent = 0; i_agent < nbrAgent; i_agent++) {
- agents.add(new Ant(i_agent, eval, env, evaporation));
- }
-
- env.initAgents(agents);
-
- res += findSolution(nbrAgent, env, eval, agents);
- System.out.println("run : "+i);
- System.out.println("Nbr eval :"+eval.getCount());
- }
- long estimatedTime = System.currentTimeMillis() - startTime;
-
- System.out.println("Time : "+estimatedTime/1000+ "s "+estimatedTime%1000+"ms");
- System.out.println(res);
- System.out.println("Average cycle : "+(double)res/(double)nbrTry);
-
- }
-
- private static int findSolution(
- int nbrAgent,
- Env env,
- Eval eval,
- List<Ant> agents
- ) {
-
- // [RUN]
-
- int cycle = 0;
-
- do {
- do {
- for (Ant agent : agents) {
- agent.perceive();
- }
- for (Ant agent : agents) {
- agent.decide();
- agent.act();
-
- }
- cycle++;
- }while (agents.get(0).getPhase() != Phase.EVALUATE);
- cycle ++;
- System.out.println("Cycle : "+cycle+" Value : "+env.bestValue());
-
- /*
- // Pas à Pas
- try {
- System.in.read();
- } catch (IOException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
- */
-
-
- } while(Math.abs(env.bestValue()-eval.getObjective())>eval.getErrorDelta());
-
- return cycle;
-
- }
-
- private static int findSolution2(
- int nbrAgent,
- Env env,
- Eval eval,
- List<Ant> agents
- ) {
-
- // [RUN]
- Scheduler scheduler = new Scheduler(env, eval, agents.toArray(new Ant[agents.size()]));
- scheduler.start();
-
- scheduler.waitUntilFinish();
-
- return scheduler.getNbOfCycles();
- }
-
-}
\ No newline at end of file
diff --git a/ant/Scheduler.java b/ant/Scheduler.java
deleted file mode 100644
index 327ce49f6a6da9e399d269d663ba43c760822c48..0000000000000000000000000000000000000000
--- a/ant/Scheduler.java
+++ /dev/null
@@ -1,28 +0,0 @@
-package ant;
-
-import java.util.List;
-
-import eval.Eval;
-import mas.core.ThreeStepCyclable;
-import mas.implementation.schedulers.variations.ThreeStepCycling;
-
-public class Scheduler extends ThreeStepCycling{
-
- public Env env;
- public Eval eval;
-
-
- public Scheduler(Env _env, Eval _eval, ThreeStepCyclable... _threeStepCyclables) {
- super(_threeStepCyclables);
- env = _env;
- eval = _eval;
- }
-
- @Override
- public boolean stopCondition() {
- if (env.getAgents().get(0).getPhase() != Phase.EVALUATE) {
- return false;
- }
- return Math.abs(env.bestValue()-eval.getObjective())<=eval.getErrorDelta();
- }
-}
\ No newline at end of file
diff --git a/baseOptiAgent/Cycle.java b/baseOptiAgent/Cycle.java
new file mode 100644
index 0000000000000000000000000000000000000000..2d2566ed697069363ffa27dc38c6932f02d842e6
--- /dev/null
+++ b/baseOptiAgent/Cycle.java
@@ -0,0 +1,21 @@
+package baseOptiAgent;
+
+public class Cycle {
+
+ private int eval;
+ private double bestSolution;
+
+ public Cycle(int _eval, double _bestSolution) {
+ eval = _eval;
+ bestSolution = _bestSolution;
+ }
+
+ public double getBestSolution() {
+ return bestSolution;
+ }
+
+ public int getEval() {
+ return eval;
+ }
+
+}
diff --git a/ihm/Ihm.java b/baseOptiAgent/Ihm.java
similarity index 52%
rename from ihm/Ihm.java
rename to baseOptiAgent/Ihm.java
index f86b58646bc1b3bc9332e0d799872f540bd5b721..ac5b1384cb4fdfa785edf8831dbbbe52233f431e 100644
--- a/ihm/Ihm.java
+++ b/baseOptiAgent/Ihm.java
@@ -1,6 +1,10 @@
-package ihm;
+package baseOptiAgent;
-import baseOptiAgent.Solver;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.util.stream.Stream;
+
+import ant.AntSolver;
import bee.BeeSolver;
import eval.Eval;
import eval.fun.Rastrigin;
@@ -16,15 +20,39 @@ public class Ihm {
int maxEval = 1000000;
Solver solver = new BeeSolver(eval, maxCycle, maxEval);
+ //Solver solver = new AntSolver(eval, maxCycle, maxEval);
+
Result res = solver.solve();
System.out.println("Cycle : "+res.totalCycle+" Out of "+maxCycle);
System.out.println("Eval : "+res.totalEval+" Out of "+maxEval);
System.out.println("Solution found "+res.optiFound);
+ /*
System.out.println("Solution : ");
for (Integer name: res.cycle.keySet()) {
System.out.println(name + " " + res.cycle.get(name));
}
+ */
+
+ writeEval(res);
+
+ }
+
+ private static void writeEval(Result res) {
+ try {
+ FileWriter csvWriter = new FileWriter("eval_"+res.name+".csv");
+ csvWriter.append("cycle,eval,sol\n");
+
+
+ for (Integer name: res.cycle.keySet()) {
+ csvWriter.append(name+","+res.cycle.get(name).getEval()+","+res.cycle.get(name).getBestSolution()+"\n");
+ }
+ csvWriter.flush();
+ csvWriter.close();
+ } catch (IOException e) {
+ // TODO Auto-generated catch block
+ e.printStackTrace();
+ }
}
}
diff --git a/ihm/Result.java b/baseOptiAgent/Result.java
similarity index 73%
rename from ihm/Result.java
rename to baseOptiAgent/Result.java
index b6dd96db994e498f236339e43261f15b8063e0f8..ef1e12711be7b3fa1257c690e6428497f149af02 100644
--- a/ihm/Result.java
+++ b/baseOptiAgent/Result.java
@@ -1,4 +1,4 @@
-package ihm;
+package baseOptiAgent;
import java.util.HashMap;
import java.util.Map;
@@ -13,12 +13,12 @@ public class Result {
public boolean optiFound;
- public Map<Integer, Double> cycle;
+ public Map<Integer, Cycle> cycle;
public Result(String _name) {
name = _name;
optiFound = false;
- cycle = new TreeMap<Integer, Double>();
+ cycle = new TreeMap<Integer, Cycle>();
}
}
diff --git a/baseOptiAgent/Solver.java b/baseOptiAgent/Solver.java
index 3b9859d7dcde918237f248e99a1c61dcca8a4201..4fe866f9fdbdbf75ecad6881c1d3c6cbabc115e6 100644
--- a/baseOptiAgent/Solver.java
+++ b/baseOptiAgent/Solver.java
@@ -3,7 +3,6 @@ package baseOptiAgent;
import java.util.List;
import eval.Eval;
-import ihm.Result;
public abstract class Solver {
@@ -29,10 +28,10 @@ public abstract class Solver {
int cycle = 0;
- res.cycle.put(0, env.getBestEval());
double bestEval = env.getBestEval();
do {
+ res.cycle.put(cycle, new Cycle(eval.getCount(), env.getBestEval()));
for(int i = 0; i < cycleModulo; i++) {
for (BaseAgent agent : agents) {
agent.perceive();
@@ -44,8 +43,8 @@ public abstract class Solver {
}
double nextEval = env.getBestEval();
+
if (nextEval < bestEval) {
- res.cycle.put(cycle, env.getBestEval());
bestEval = nextEval;
}
diff --git a/bee/BeeSolver.java b/bee/BeeSolver.java
index 63ef6cf30fdc1a4434b73e3a7ee6a5a42f55a686..b44bf082a0190787a5cee66a1442c1ed1916519b 100644
--- a/bee/BeeSolver.java
+++ b/bee/BeeSolver.java
@@ -5,9 +5,9 @@ import java.util.List;
import baseOptiAgent.BaseAgent;
import baseOptiAgent.Env;
+import baseOptiAgent.Result;
import baseOptiAgent.Solver;
import eval.Eval;
-import ihm.Result;
public class BeeSolver extends Solver{
diff --git a/bee/MainBee.java b/bee/MainBee.java
deleted file mode 100644
index 907e7271bc6a466064584ca6f28d32aecae8a9c0..0000000000000000000000000000000000000000
--- a/bee/MainBee.java
+++ /dev/null
@@ -1,105 +0,0 @@
-package bee;
-
-import java.io.IOException;
-import java.util.ArrayList;
-import java.util.List;
-
-import eval.Eval;
-import eval.fun.Rastrigin;
-import eval.fun.SchwefelFunction1_2;
-import eval.fun.StepFunction;
-
-public class MainBee {
- public static void main(String[] args) {
- // [PARAM]
-
- int nbrAgent = 100;
- int maxTry = 200;
-
- int res = 0;
- int nbrTry = 1;
-
- long startTime = System.currentTimeMillis();
- for (int i = 0; i < nbrTry; i++) {
- // [INIT]
-
- //Eval eval = new StepFunction();
- //Eval eval = new SchwefelFunction1_2();
- //Eval eval = new SchwefelFunction();
- Eval eval = new Rastrigin();
-
-
- BeeEnv env = new BeeEnv();
-
- List<Bee> agents = new ArrayList<Bee>();
- for (int i_agent = 0; i_agent < nbrAgent; i_agent++) {
- agents.add(new Bee(i_agent, eval, env, maxTry));
- }
-
- env.initAgent(agents);
-
- res += findSolution(nbrAgent, env, eval, agents);
- System.out.println("run : "+i);
- System.out.println("Nbr eval :"+eval.getCount());
- }
- long estimatedTime = System.currentTimeMillis() - startTime;
-
- System.out.println("Time : "+estimatedTime/1000+ "s "+estimatedTime%1000+"ms");
- System.out.println(res);
- System.out.println("Average cycle : "+(double)res/(double)nbrTry);
-
- }
-
- private static int findSolution(
- int nbrAgent,
- BeeEnv env,
- Eval eval,
- List<Bee> agents
- ) {
-
- // [RUN]
-
- int cycle = 0;
- double bestSol = 0;
-
- do {
- do {
- for (Bee agent : agents) {
- agent.perceive();
- }
- for (Bee agent : agents) {
- agent.decide();
- agent.act();
-
- }
- }while (agents.get(0).getPhase() != Phase.EMPLOYED);
-
- if(cycle == 0) {
- bestSol = env.getBestEval();
- }
- else if (env.getBestEval() < bestSol) {
- bestSol = env.getBestEval();
- System.out.println("Improve : "+bestSol+" at :"+cycle);
- }
-
- cycle ++;
- //System.out.println("Cycle : "+cycle+" Value : "+env.bestEval());
-
- /*
- // Pas à Pas
- try {
- System.in.read();
- } catch (IOException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
- */
-
-
-
- } while(Math.abs(env.getBestEval()-eval.getObjective())>eval.getErrorDelta());
-
- return cycle;
-
- }
-}