babylon.config.defines.survival

Survival calculus (P(S|A), P(S|R)) and Agency-Layer struggle dynamics.

Spec 058: extracted from the historical babylon.config.defines monolith. Re-exported via babylon.config.defines.__init__; composed into GameDefines in babylon.config.defines._assembler.

Classes

AidDefines(**data)	AID verb coefficients.
BehavioralDefines(**data)	Behavioral economics coefficients.
StruggleDefines(**data)	Struggle dynamics coefficients (Agency Layer - "George Floyd" Dynamic).
SurvivalDefines(**data)	Survival calculus coefficients.
TensionDefines(**data)	Tension dynamics coefficients.
VitalityDefines(**data)	Mortality coefficients for Mass Line population dynamics.

class babylon.config.defines.survival.AidDefines(**data)

Bases: BaseModel

AID verb coefficients.

Parameters:

• aid_efficiency (float)

• aid_cl_cost (float)

• aid_solidarity_increment (float)

• solidaristic_threshold (float)

• education_threshold_for_solidarity (float)

• agitation_relief_per_unit (float)

• economism_warning_threshold (float)

aid_efficiency: float

aid_cl_cost: float

aid_solidarity_increment: float

solidaristic_threshold: float

education_threshold_for_solidarity: float

agitation_relief_per_unit: float

economism_warning_threshold: float

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class babylon.config.defines.survival.BehavioralDefines(**data)

Bases: BaseModel

Behavioral economics coefficients.

Parameters:

loss_aversion_lambda (float)

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

loss_aversion_lambda: float

class babylon.config.defines.survival.StruggleDefines(**data)

Bases: BaseModel

Struggle dynamics coefficients (Agency Layer - “George Floyd” Dynamic).

The Struggle System gives political agency to oppressed classes by modeling: - The Spark: State violence (EXCESSIVE_FORCE) triggers insurrection - The Combustion: Spark + High Agitation + Low P(S|A) = UPRISING - The Result: Uprisings destroy wealth but build solidarity infrastructure

George Jackson Bifurcation (Power Vacuum): When the Comprador becomes insolvent, a power vacuum occurs. The outcome depends on the Periphery Proletariat’s revolutionary capacity: - capacity >= jackson_threshold: Revolutionary Offensive - capacity < jackson_threshold: Fascist Revanchism

Parameters:

• spark_probability_scale (float)

• resistance_threshold (float)

• wealth_destruction_rate (float)

• solidarity_gain_per_uprising (float)

• consciousness_solidarity_boost (float)

• jackson_threshold (float)

• revolutionary_agitation_boost (float)

• fascist_identity_boost (float)

• fascist_acquiescence_boost (float)

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

spark_probability_scale: float

resistance_threshold: float

wealth_destruction_rate: float

solidarity_gain_per_uprising: float

consciousness_solidarity_boost: float

jackson_threshold: float

revolutionary_agitation_boost: float

fascist_identity_boost: float

fascist_acquiescence_boost: float

class babylon.config.defines.survival.SurvivalDefines(**data)

Bases: BaseModel

Survival calculus coefficients.

Parameters:

• steepness_k (float)

• default_subsistence (float)

• default_organization (float)

• default_repression (float)

• revolution_threshold (float)

• repression_base (float)

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

steepness_k: float

default_subsistence: float

default_organization: float

default_repression: float

revolution_threshold: float

repression_base: float

class babylon.config.defines.survival.TensionDefines(**data)

Bases: BaseModel

Tension dynamics coefficients.

Parameters:

• accumulation_rate (float)

• aspect_flip_threshold (float)

• antagonistic_intensity_threshold (float)

• resolution_intensity_threshold (float)

• rupture_gap_threshold (float)

• principal_rate_weight (float)

• regime_rate_epsilon (float)

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

accumulation_rate: float

aspect_flip_threshold: float

antagonistic_intensity_threshold: float

resolution_intensity_threshold: float

rupture_gap_threshold: float

principal_rate_weight: float

regime_rate_epsilon: float

class babylon.config.defines.survival.VitalityDefines(**data)

Bases: BaseModel

Mortality coefficients for Mass Line population dynamics.

The Grinding Attrition Formula models probabilistic mortality based on intra-class inequality: - Even with sufficient average wealth, high inequality kills marginal workers - Deaths reduce population → per-capita wealth increases → equilibrium

Formula:

effective_wealth_per_capita = wealth / population marginal_wealth = effective_wealth_per_capita × (1 - inequality × inequality_impact) mortality_rate = max(0, (consumption_needs - marginal_wealth) / consumption_needs) deaths = floor(population × mortality_rate × base_mortality_factor)

Malthusian Correction: Population decline increases per-capita wealth, reducing future mortality rates and creating equilibrium dynamics.

Parameters:

• base_mortality_factor (float)

• inequality_impact (float)

• attrition_base_factor (float)

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

base_mortality_factor: float

inequality_impact: float

attrition_base_factor: float