map.getConcepts().get("efactors").setFixedOutput(false);
InputLearningConcept ped = new InputLearningConcept();
ped.setName("pediatrician");
ped.setFixedOutput(true);
ped.setTrainingFunction(new LinearBP());
map.addConcept(ped);
LearningWeightedConnection conn1 = new LearningWeightedConnection();
conn1.setName("ped_ability");
conn1.setFrom(ped);
conn1.setTo(map.getConcept("static_ability"));
conn1.setWeight(0.9);
map.addConnection(conn1);
map.connect(conn1.getFrom().getName(), conn1.getName(), conn1.getTo().getName());
InputLearningConcept ent = new InputLearningConcept();
ent.setName("ent");
ent.setFixedOutput(true);
ent.setTrainingFunction(new LinearBP());
map.addConcept(ent);
LearningWeightedConnection conn10 = new LearningWeightedConnection();
conn10.setName("ent_ability");
conn10.setFrom(ent);
conn10.setTo(map.getConcept("static_ability"));
conn10.setWeight(0.3);
map.addConnection(conn10);
map.connect(conn10.getFrom().getName(), conn10.getName(), conn10.getTo().getName());
InputLearningConcept cautious = new InputLearningConcept();
cautious.setName("cautious");
cautious.setOutput(1.0);
cautious.setFixedOutput(true);
cautious.setTrainingFunction(new LinearBP());
map.addConcept(cautious);
LearningWeightedConnection conn2 = new LearningWeightedConnection();
conn2.setName("cautious_disposition");
conn2.setFrom(cautious);
conn2.setTo(map.getConcept("static_disposition"));
conn2.setWeight(0.9);
map.addConnection(conn2);
map.connect(conn2.getFrom().getName(), conn2.getName(), conn2.getTo().getName());
InputLearningConcept female = new InputLearningConcept();
female.setName("female");
female.setOutput(1.0);
female.setFixedOutput(true);
female.setTrainingFunction(new LinearBP());
map.addConcept(female);
LearningWeightedConnection conn3 = new LearningWeightedConnection();
conn3.setName("female_cross");
conn3.setFrom(female);
conn3.setTo(map.getConcept("cross"));