#917 -Finished integrating all agents to either train (policy agents) or evaluate (hard-coded agents). Still some fixing up to do, tidying up, loading etc. also docs. But this is all now working.

src/primaite/common/enums.py

@@ -32,6 +32,7 @@ class Priority(Enum):
 class HardwareState(Enum):
     """Node hardware state enumeration."""
 
+    NONE = 0
     ON = 1
     OFF = 2
     RESETTING = 3
@@ -42,6 +43,7 @@ class HardwareState(Enum):
 class SoftwareState(Enum):
     """Software or Service state enumeration."""
 
+    NONE = 0
     GOOD = 1
     PATCHING = 2
     COMPROMISED = 3
@@ -94,7 +96,8 @@ class VerboseLevel(IntEnum):
 
 
 class AgentFramework(Enum):
-    NONE = 0
+    """The agent algorithm framework/package."""
+    CUSTOM = 0
     "Custom Agent"
     SB3 = 1
     "Stable Baselines3"
@@ -103,7 +106,7 @@ class AgentFramework(Enum):
 
 
 class DeepLearningFramework(Enum):
-    """The deep learning framework enumeration."""
+    """The deep learning framework."""
     TF = "tf"
     "Tensorflow"
     TF2 = "tf2"
@@ -112,15 +115,28 @@ class DeepLearningFramework(Enum):
     "PyTorch"
 
 
-class RedAgentIdentifier(Enum):
+class AgentIdentifier(Enum):
+    """The Red Agent algo/class."""
     A2C = 1
     "Advantage Actor Critic"
     PPO = 2
     "Proximal Policy Optimization"
     HARDCODED = 3
-    "Custom Agent"
-    RANDOM = 4
-    "Custom Agent"
+    "The Hardcoded agents"
+    DO_NOTHING = 4
+    "The DoNothing agents"
+    RANDOM = 5
+    "The RandomAgent"
+    DUMMY = 6
+    "The DummyAgent"
+
+
+class HardCodedAgentView(Enum):
+    """The view the deterministic hard-coded agent has of the environment."""
+    BASIC = 1
+    "The current observation space only"
+    FULL = 2
+    "Full environment view with actions taken and reward feedback"
 
 
 class ActionType(Enum):