Enhance cognition progress calculation with weighted metrics and impr…

…ove reporting format; add unit tests for new functionality

models/consciousness_model.py

@@ -209,12 +209,32 @@ def adaptive_learning_step(self, state: torch.Tensor, error: float) -> torch.Ten
 
     def calculate_cognition_progress(self, metrics):
         """
-        Calculate the percentage of cognition achieved based on metrics.
+        Calculate the percentage of cognition achieved based on multiple metrics.
         """
-        # Example calculation based on 'phi' metric
-        phi = metrics.get('phi', 0)
-        cognition_percentage = phi * 100
-        self.cognition_progress_history.append(cognition_percentage)
+        scores = {
+            'phi': metrics.get('phi', 0),
+            'coherence': metrics.get('coherence', 0),
+            'stability': metrics.get('stability', 0),
+            'adaptability': metrics.get('adaptability', 0),
+            'memory_retention': metrics.get('memory_retention', 0)
+        }
+
+        weights = {
+            'phi': 0.3,
+            'coherence': 0.2,
+            'stability': 0.15,
+            'adaptability': 0.15,
+            'memory_retention': 0.2
+        }
+
+        weighted_score = sum(weights[k] * scores[k] for k in weights)
+        cognition_percentage = weighted_score * 100
+
+        self.cognition_progress_history.append({
+            'total': cognition_percentage,
+            'breakdown': scores
+        })
+
         return cognition_percentage
 
     def report_cognition_progress(self):
@@ -223,25 +243,24 @@ def report_cognition_progress(self):
         """
         if not self.cognition_progress_history:
             return "No cognition progress data available."
-
-        avg_progress = sum(self.cognition_progress_history) / len(self.cognition_progress_history)
-        areas_to_improve = []
-
-        # Example criteria for identifying areas to improve
-        if avg_progress < 50:
-            areas_to_improve.append("Increase phi metric to improve cognition progress.")
-        if 'context_stability' in self.metrics and self.metrics['context_stability'] < 0.5:
-            areas_to_improve.append("Improve context stability.")
-        if 'coherence' in self.metrics and self.metrics['coherence'] < 0.5:
-            areas_to_improve.append("Enhance coherence in state transitions.")
-
-        report = f"Average Cognition Progress: {avg_progress}%\n"
-        if areas_to_improve:
-            report += "Areas to Improve:\n" + "\n".join(areas_to_improve)
-        else:
-            report += "All areas are performing well."
-
-        return report
+
+        latest = self.cognition_progress_history[-1]
+        report = [
+            f"Current Cognition Progress: {latest['total']:.2f}%\n",
+            "Breakdown:",
+            f"- Integrated Information (Phi): {latest['breakdown']['phi']*100:.2f}%",
+            f"- Thought Coherence: {latest['breakdown']['coherence']*100:.2f}%",
+            f"- Context Stability: {latest['breakdown']['stability']*100:.2f}%",
+            f"- Adaptability: {latest['breakdown']['adaptability']*100:.2f}%",
+            f"- Memory Retention: {latest['breakdown']['memory_retention']*100:.2f}%\n",
+            "Areas Needing Improvement:"
+        ]
+
+        for metric, value in latest['breakdown'].items():
+            if value < 0.6:
+                report.append(f"- {metric.replace('_', ' ').title()}")
+
+        return "\n".join(report)
 
     def forward(self, inputs, state=None, initial_state=None, deterministic=True, consciousness_threshold=0.5):
         """

test.txt

@@ -2,19 +2,19 @@
 platform linux -- Python 3.10.12, pytest-8.3.4, pluggy-1.5.0
 rootdir: /home/kasinadhsarma/experiment/cognition-l3-experiment
 plugins: cov-6.0.0, anyio-4.7.0
-collected 114 items
+collected 115 items
 
 tests/benchmarks/test_arc_reasoning.py .......                           [  6%]
 tests/benchmarks/test_bigbench_reasoning.py .....                        [ 10%]
-tests/test_consciousness.py ............................                 [ 35%]
-tests/test_environment.py .....s..                                       [ 42%]
+tests/test_consciousness.py ............................                 [ 34%]
+tests/test_environment.py ......s..                                      [ 42%]
 tests/test_error_correction.py .........                                 [ 50%]
 tests/unit/attention/test_attention.py ......                            [ 55%]
 tests/unit/attention/test_attention_mechanisms.py .......                [ 61%]
 tests/unit/integration/test_cognitive_integration.py ......              [ 66%]
-tests/unit/integration/test_state_management.py ......                   [ 71%]
+tests/unit/integration/test_state_management.py ......                   [ 72%]
 tests/unit/memory/test_integration.py ......                             [ 77%]
-tests/unit/memory/test_memory.py ..........                              [ 85%]
+tests/unit/memory/test_memory.py ..........                              [ 86%]
 tests/unit/memory/test_memory_components.py ..........                   [ 94%]
 tests/unit/state/test_consciousness_state_management.py ......           [100%]
 
@@ -24,4 +24,4 @@ tests/unit/state/test_consciousness_state_management.py ......           [100%]
     _C._set_default_tensor_type(t)
 
 -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
-================== 113 passed, 1 skipped, 1 warning in 8.94s ===================
+================== 114 passed, 1 skipped, 1 warning in 10.78s ==================

tests/unit/test_cognition_progress.py

@@ -0,0 +1,43 @@
+
+import pytest
+import torch
+from models.consciousness_model import ConsciousnessModel
+
+class TestCognitionProgress:
+    @pytest.fixture
+    def model(self):
+        config = ConsciousnessModel.create_default_config()
+        return ConsciousnessModel(**config)
+
+    def test_cognition_progress_initial(self, model):
+        assert len(model.cognition_progress_history) == 0
+
+    def test_calculate_cognition_progress(self, model):
+        metrics = {
+            'phi': 0.7,
+            'coherence': 0.8,
+            'stability': 0.65,
+            'adaptability': 0.75,
+            'memory_retention': 0.85
+        }
+        progress = model.calculate_cognition_progress(metrics)
+        expected = (0.3 * 0.7) + (0.2 * 0.8) + (0.15 * 0.65) + (0.15 * 0.75) + (0.2 * 0.85)
+        assert progress == pytest.approx(expected * 100)
+        assert len(model.cognition_progress_history) == 1
+
+    def test_report_cognition_progress_no_data(self, model):
+        report = model.report_cognition_progress()
+        assert report == "No cognition progress data available."
+
+    def test_report_cognition_progress_with_data(self, model):
+        metrics = {
+            'phi': 0.7,
+            'coherence': 0.8,
+            'stability': 0.65,
+            'adaptability': 0.75,
+            'memory_retention': 0.85
+        }
+        model.calculate_cognition_progress(metrics)
+        report = model.report_cognition_progress()
+        assert "Current Cognition Progress: 75.00%" in report
+        assert "Areas Needing Improvement:" in report