Bases: ArbitrationPolicy
Static Arbitration Policy for the Reasoner module.
This class implements a fixed priority arbitration mechanism for
SA (Situational Awareness) components. Each SA component category
is assigned a static weight representing its priority level.
In case of conflicting SA commands, the policy selects the command
whose originating component has the highest priority weight.
Attributes:
| Name |
Type |
Description |
_verbose |
bool
|
Enables verbose logging for debugging and tracing.
|
agent_weights |
dict
|
Mapping of SA component categories to static weights.
|
Methods:
| Name |
Description |
init |
Placeholder for initialization with external configuration.
|
tie_break |
Resolves conflicts between two SA commands by
comparing their category weights, returning True if sac1 wins.
|
Source code in nebula/core/situationalawareness/awareness/arbitrationpolicies/staticarbitrationpolicy.py
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67 | class SAP(ArbitrationPolicy): # Static Arbitatrion Policy
"""
Static Arbitration Policy for the Reasoner module.
This class implements a fixed priority arbitration mechanism for
SA (Situational Awareness) components. Each SA component category
is assigned a static weight representing its priority level.
In case of conflicting SA commands, the policy selects the command
whose originating component has the highest priority weight.
Attributes:
_verbose (bool): Enables verbose logging for debugging and tracing.
agent_weights (dict): Mapping of SA component categories to static weights.
Methods:
init(config): Placeholder for initialization with external configuration.
tie_break(sac1, sac2): Resolves conflicts between two SA commands by
comparing their category weights, returning True if sac1 wins.
"""
def __init__(self, verbose):
self._verbose = verbose
# Define static weights for SA Agents from SA Components
self.agent_weights = {"SATraining": 1, "SANetwork": 2, "SAReputation": 3}
async def init(self, config):
pass
async def _get_agent_category(self, sa_command: SACommand) -> str:
"""
Extract agent category name.
Example: "SATraining_Agent1" → "SATraining"
"""
full_name = await sa_command.get_owner()
return full_name.split("_")[0] if "_" in full_name else full_name
async def tie_break(self, sac1: SACommand, sac2: SACommand) -> bool:
"""
Tie break conflcited SA Commands
"""
if self._verbose:
logging.info(
f"Tie break between ({await sac1.get_owner()}, {sac1.get_action().value}) & ({await sac2.get_owner()}, {sac2.get_action().value})"
)
async def get_weight(cmd):
category = await self._get_agent_category(cmd)
return self.agent_weights.get(category, 0)
if await get_weight(sac1) > await get_weight(sac2):
if self._verbose:
logging.info(
f"Tie break resolved, SA Command choosen ({await sac1.get_owner()}, {sac1.get_action().value})"
)
return True
else:
if self._verbose:
logging.info(
f"Tie break resolved, SA Command choosen ({await sac2.get_owner()}, {sac2.get_action().value})"
)
return False
|
tie_break(sac1, sac2)
async
Tie break conflcited SA Commands
Source code in nebula/core/situationalawareness/awareness/arbitrationpolicies/staticarbitrationpolicy.py
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67 | async def tie_break(self, sac1: SACommand, sac2: SACommand) -> bool:
"""
Tie break conflcited SA Commands
"""
if self._verbose:
logging.info(
f"Tie break between ({await sac1.get_owner()}, {sac1.get_action().value}) & ({await sac2.get_owner()}, {sac2.get_action().value})"
)
async def get_weight(cmd):
category = await self._get_agent_category(cmd)
return self.agent_weights.get(category, 0)
if await get_weight(sac1) > await get_weight(sac2):
if self._verbose:
logging.info(
f"Tie break resolved, SA Command choosen ({await sac1.get_owner()}, {sac1.get_action().value})"
)
return True
else:
if self._verbose:
logging.info(
f"Tie break resolved, SA Command choosen ({await sac2.get_owner()}, {sac2.get_action().value})"
)
return False
|