ArgmaxNoiseScenario
Agents scenarios · Implementation: mlsysim/engine/scenario_definitions/agents.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
Argmax over equally good candidates with Gaussian score noise; a rare loophole in the pool.
Notes
Equation: result = ArgmaxNoiseModel.solve(…) with the declared pool_sizes, small_pool, large_pool inputs.
Assumptions: The inputs instantiate the assumptions documented by mlsysim.solvers.ArgmaxNoiseModel.solve; accessing result evaluates that solver again.
Excludes: Any extra mechanism beyond ArgmaxNoiseModel; this record supplies configuration and does not collect performance measurements.
References
Derivation: This configuration forwards its stored inputs to mlsysim.solvers.ArgmaxNoiseModel.solve. The solver contract records the equations and their provenance.
Examples
The named scenario supplies illustrative inputs; the output is calculated.
>>> from mlsysim import Scenarios
>>> case = Scenarios.ArgmaxScoreNoise
>>> round(float(case.result.exploit_presence), 3)
0.274Attributes
| Name | Description |
|---|---|
| exploit_rate | |
| large_pool | |
| pool_sizes | |
| result | Modeled result from mlsysim.solvers.ArgmaxNoiseModel.solve using this |
| small_pool |
pool_sizes
Type: List[int].
Declared default: required.
small_pool
Type: int.
Declared default: required.
large_pool
Type: int.
Declared default: required.
exploit_rate
Type: float.
Declared default: required.
result
engine.scenario_types.ArgmaxNoiseScenario.result
Modeled result from mlsysim.solvers.ArgmaxNoiseModel.solve using this scenario’s declared inputs; see that method for units, limits, and feasibility.
Equation: Delegates the declared fields to mlsysim.solvers.ArgmaxNoiseModel.solve; returned quantities and feasibility follow that contract.