Implement Policy-Bound Semantic Memory Layer

examples/run_simulation.py

@@ -51,7 +51,7 @@ def main() -> None:
         np.ones(12) * 3.5,  # Extreme excitation (Red)
         np.ones(12) * 5.0,  # Extreme excitation (Red)
         np.ones(12) * 0.1,  # Dissipation / Recovery phase
-        np.ones(12) * 0.05, # Dissipation
+        np.ones(12) * 0.05,  # Dissipation
         np.ones(12) * 0.01  # Fully dissipated / Recovered
     ]
 
@@ -94,12 +94,12 @@ def main() -> None:
     # Let's run steps with escalating compliance degradation and cost load
     multi_task_values = [0.9, 0.9, 0.9, 0.8, 0.8, 0.5]
     multi_excitations = [
-        np.ones(12) * 0.5, # Nominal (Green)
-        np.ones(12) * 0.5, # Nominal (Green)
-        np.ones(12) * 1.5, # Mid excitation (Yellow)
-        np.ones(12) * 3.0, # High tension (Red)
-        np.ones(12) * 4.5, # High tension (Red)
-        np.ones(12) * 0.1, # Safe mode recovery
+        np.ones(12) * 0.5,  # Nominal (Green)
+        np.ones(12) * 0.5,  # Nominal (Green)
+        np.ones(12) * 1.5,  # Mid excitation (Yellow)
+        np.ones(12) * 3.0,  # High tension (Red)
+        np.ones(12) * 4.5,  # High tension (Red)
+        np.ones(12) * 0.1,  # Safe mode recovery
     ]
 
     # Dynamically inject bad policy/compliance & high latencies on step 3 to trigger red band and quarantine

radial_membrane_ai/boundary.py

@@ -9,7 +9,7 @@
 
 from __future__ import annotations
 import math
-from radial_membrane_ai.membrane import RadialMembrane, BehavioralString
+from radial_membrane_ai.membrane import RadialMembrane
 from radial_membrane_ai.channels import channel_coherence
 from radial_membrane_ai.admissibility import angular_decomposition
 from radial_membrane_ai.projection import closure_ratio

radial_membrane_ai/channels.py

@@ -12,7 +12,7 @@
 import numpy as np
 
 from radial_membrane_ai.membrane import BehavioralString, RadialMembrane
-from radial_membrane_ai.facet import route_signal, FacetVector, TensionState
+from radial_membrane_ai.facet import route_signal
 
 
 def phase_alignment(theta_s: float, theta_t: float) -> float:

radial_membrane_ai/cost.py

@@ -6,8 +6,7 @@
 """
 
 from __future__ import annotations
-from dataclasses import dataclass, replace
-import math
+from dataclasses import dataclass
 
 
 @dataclass(frozen=True)

radial_membrane_ai/envelope.py

@@ -15,13 +15,11 @@
 from __future__ import annotations
 import math
 from typing import TYPE_CHECKING, Dict, Any, List, Tuple
-import numpy as np
-
 if TYPE_CHECKING:
     from radial_membrane_ai.membrane import RadialMembrane
     from radial_membrane_ai.boundary import BoundaryGeometry
 
-from radial_membrane_ai.projection import closure_ratio, project_to_admissible, residual_deformation
+from radial_membrane_ai.projection import project_to_admissible, residual_deformation
 from radial_membrane_ai.admissibility import angular_projections, dynamic_capacity_boundary
 
 

radial_membrane_ai/governor.py

@@ -7,7 +7,7 @@
 
 from __future__ import annotations
 import math
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 import numpy as np
 
 from radial_membrane_ai.membrane import BehavioralString, RadialMembrane

radial_membrane_ai/mesh.py

@@ -8,12 +8,15 @@
 - Holistic Mesh Governor
 
 And calculates the global mesh coherence score:
-C_mesh(t) = normalize(w_q * Q_route + w_t * T_trust + w_e * E_economic - w_r * R_residual - w_p * P_policy - w_l * L_latency - w_f * F_failure)
+C_mesh(t) = normalize(
+    w_q * Q_route + w_t * T_trust + w_e * E_economic -
+    w_r * R_residual - w_p * P_policy - w_l * L_latency - w_f * F_failure
+)
 """
 
 from __future__ import annotations
 import numpy as np
-from typing import List, Dict, Any, Optional
+from typing import List, Dict, Any
 from radial_membrane_ai.shard import FederatedShard, ShardState
 from radial_membrane_ai.residuals import ResidualLedger
 from radial_membrane_ai.routing import FederatedRoutingChannel
@@ -134,7 +137,10 @@ def compute_mesh_coherence(
     ) -> float:
         """
         Computes the global mesh coherence score:
-        C_mesh(t) = normalize(w_q * Q_route + w_t * T_trust + w_e * E_economic - w_r * R_residual - w_p * P_policy - w_l * L_latency - w_f * F_failure)
+        C_mesh(t) = normalize(
+            w_q * Q_route + w_t * T_trust + w_e * E_economic -
+            w_r * R_residual - w_p * P_policy - w_l * L_latency - w_f * F_failure
+        )
         """
         if not self.shards:
             return 1.0

radial_membrane_ai/multi_agent/governance.py

@@ -142,7 +142,7 @@ def execute_sao_promotion(
 
         # 3. Admissibility test against shared capacity
         # Find maximum activation in the aligned state
-        max_act = float(np.max(x_sym))
+        _ = float(np.max(x_sym))
 
         # 4. Projection P(x_sym)
         # Projects to admissible space: clamp to shared_capacity_limit

radial_membrane_ai/multi_agent/simulation.py

@@ -4,7 +4,7 @@
 
 from __future__ import annotations
 import numpy as np
-from typing import Dict, Any, List
+from typing import Dict, List
 
 from radial_membrane_ai.multi_agent.agent import UFOAgent
 from radial_membrane_ai.multi_agent.coupling import InterAgentVChannel, GlobalHolisticGovernor
@@ -140,7 +140,10 @@ def run_step(self, scenario_type: str, task_value: float = 0.8) -> None:
                     s.activation *= 0.85
         else:
             # Red band: Hard interventions (heavy throttling, quarantine, fallback)
-            self.intervention_log.append(f"Hard Intervention (Red Band): C_mesh={c_mesh:.4f}. Throttling, Quarantining, and Fallback.")
+            self.intervention_log.append(
+                f"Hard Intervention (Red Band): C_mesh={c_mesh:.4f}. "
+                "Throttling, Quarantining, and Fallback."
+            )
             # Throttle activations heavily
             for agent in self.agents:
                 for s in agent.membrane.strings:
@@ -163,7 +166,9 @@ def run_step(self, scenario_type: str, task_value: float = 0.8) -> None:
                 if agent_l.shard.state != ShardState.QUARANTINED and agent_r.shard.state != ShardState.QUARANTINED:
                     # Shared capacity limit is dynamically modulated by mesh coherence
                     limit = max(0.02, 0.5 * c_mesh)
-                    verdict, p_sao, _ = self.mesh_governance.execute_sao_promotion(agent_l, agent_r, shared_capacity_limit=limit)
+                    verdict, p_sao, _ = self.mesh_governance.execute_sao_promotion(
+                        agent_l, agent_r, shared_capacity_limit=limit
+                    )
                     if verdict == "block":
                         self.intervention_log.append(
                             f"SAO Promotion Blocked between {agent_l.agent_id} and {agent_r.agent_id}. "

radial_membrane_ai/projection.py

@@ -7,7 +7,7 @@
 
 from __future__ import annotations
 import math
-from typing import Any
+
 
 def closure_ratio(a: float, b: float, c: float) -> float:
     """

radial_membrane_ai/routing.py

@@ -7,7 +7,6 @@
 
 from __future__ import annotations
 from typing import Dict, Any, List, Optional
-import math
 from radial_membrane_ai.shard import FederatedShard, ShardState
 
 

radial_membrane_ai/saopromotion.py

@@ -30,6 +30,7 @@
 
 import numpy as np
 
+
 class SAOPromotor:
     """
     Symmetric Ascension Operator (SAO) executing layer promotions.

radial_membrane_ai/semantic_memory/__init__.py

@@ -0,0 +1,59 @@
+"""
+Policy-Bound Semantic Memory Layer package.
+"""
+
+from __future__ import annotations
+
+from radial_membrane_ai.semantic_memory.policy import (
+    MemoryPolicy,
+    AdmissibilityContext,
+    PolicyContext
+)
+from radial_membrane_ai.semantic_memory.curvature import (
+    MemoryCurvatureState
+)
+from radial_membrane_ai.semantic_memory.core import (
+    MemoryRecord,
+    MemoryEvent,
+    MemoryResult,
+    PromotionResult,
+    AgentSemanticMemory,
+    MeshSemanticMemory,
+    write_memory,
+    read_memory,
+    list_memory,
+    promote_memory,
+    read_shared_memory,
+    list_shared_memory
+)
+from radial_membrane_ai.semantic_memory.integration import (
+    bind_to_agent,
+    bind_to_mesh,
+    on_tick_start,
+    on_tick_end,
+    on_sao_promotion
+)
+
+__all__ = [
+    "MemoryPolicy",
+    "AdmissibilityContext",
+    "PolicyContext",
+    "MemoryCurvatureState",
+    "MemoryRecord",
+    "MemoryEvent",
+    "MemoryResult",
+    "PromotionResult",
+    "AgentSemanticMemory",
+    "MeshSemanticMemory",
+    "write_memory",
+    "read_memory",
+    "list_memory",
+    "promote_memory",
+    "read_shared_memory",
+    "list_shared_memory",
+    "bind_to_agent",
+    "bind_to_mesh",
+    "on_tick_start",
+    "on_tick_end",
+    "on_sao_promotion",
+]