White Paper
AFA Dynamic Lifetime Optimization Model
AFA Dynamic Lifetime Optimization Model
Formulating the maximisation of lifetime life satisfaction as a dynamic optimisation problem. The satisfaction and weight of each of eight domains, the allocation constraint on finite resources, state transitions through accumulation and depletion, and an endogenous horizon — brought into a single structure.
What is maximised is the lifetime total.
Each of the eight domains that make up a life has, at time t , a level of satisfaction and a weight allocated to it. Their product is the cross-sectional area of that instant.
Integrating the cross-section along time and summing the eight domains gives lifetime life satisfaction.
Place time t on the X axis, satisfaction s on the Y axis and weight w on the Z axis. The volume obtained by integrating the cross-section over time is the lifetime total happiness of that domain.
The allocation always sums to one.
The eight domains are 1 love / 2 wisdom / 3 fortune / 4 wealth / 5 vitality / 6 grace / 7 gratitude / 8 respect. Because time, energy and resources are finite, the weights always sum to one.
This single constraint turns the model from a list of values into a strategy. Thicken one place, and another thins. Every solution trades one domain against another. The question, then, is what to choose and what to defer.
Today’s satisfaction is set by yesterday’s allocation.
Each domain carries a state built up to that moment — accumulated love, accumulated wisdom, the state of fortune, accumulated wealth, the capital of vitality. Satisfaction arises from this state.
The state rises with allocation and declines with the passage of time.
In simple form, ẋi = αiwi(t) − βixi(t) − Di(wi(t)), where α is accumulation through input, β natural depletion, and D damage from over-allocation. Excess raises the cross-section of the moment while eroding the states that follow.
The eight domains interact: accumulated vitality reaches wealth through the capacity to work, and accumulated love reaches vitality and the state of mind. Hence Gi takes all eight states as its arguments. The model deals with eight interacting states.
The horizon, too, is the result of choice.
The upper limit of the integral, T , is endogenous. The horizon is the moment the state vector leaves the viable region.
The horizon is reached as a combination of domains: it ends when the state leaves the region Ω. States tied to vitality and the foundations of living define this boundary most strongly.
From this structure follows the central result of the model. The allocation that maximises the cross-section at one moment and the allocation that maximises the lifetime volume often differ. Over-allocation lifts the value of the moment while eroding later states and pulling the horizon itself nearer. What is lost is more than that one moment. It is the whole of the remaining interval.
The five-step chain and its mathematical counterpart.
The five-step chain the AFA Method has described for the individual corresponds one-to-one to the components of this control problem.
Destiny sets more than the initial conditions. It includes how the state moves and how wide the reachable region is. Hence the same allocation yields different results for different people.
What the OS raises is the precision of choice.
The AFA Method sets the objective function, and the Quantum Spacetime Strategy OS sharpens the precision of its optimum. Rather than deciding w(t), the OS supplies decision information for finding the allocation w*(t) that makes the objective larger.
It acts through two routes.
From above — the precision of choice
q(t) → w*(t) → U
Information from the three coordinates of person, time and space supports the choice of allocation at each moment.
From within — acting directly on fortune
q(t) → S3
For fortune, among the eight domains, the satisfaction function itself takes the information from coordinate computation as an argument. S3 = S3(x3, t ; q(t))
Being and focus belong to the person. The OS gives precision to choice — when to move, and where to choose. Its optimum differs from person to person.
The scope of the model.
Nature
This is a conceptual model that expresses the idea of lifetime accumulation through mathematical intuition. It is not a formula for measuring happiness as a physical quantity.
Measurement
Satisfaction si and state xi have no unified unit of measurement. The model provides a structure for building allocation decisions.
Functional form
Si and Gi : their specific functional forms and the boundary conditions of the region Ω lie outside the scope of this paper.
Use
Used as a structure that supports decisions. It does not replace medical, investment or legal judgement. Final decisions are made by the person, together with professional advice in each field.
Abstract
The AFA Dynamic Lifetime Optimization Model formulates lifetime life satisfaction as a dynamic resource-allocation problem. Life comprises eight domains — love, wisdom, fortune, wealth, vitality, grace, gratitude and respect. At each instant, every domain carries a satisfaction level and a weight drawn from a finite pool, and the product of the two forms a cross-sectional area. Integrating that area over time yields the volume of a domain; the sum across the eight domains is the quantity to be maximised.
Three features distinguish the model. First, the weights sum to one at every instant, so raising one domain necessarily lowers another. Second, satisfaction is not exogenous: it is a function of a state variable shaped by the entire history of past allocation, with accumulation, natural decay and damage from over-allocation all entering the law of motion. Third, the horizon itself is endogenous — it is the first time at which the state vector leaves a viable region, so present allocation can shorten the interval over which the integral is taken.
Together these imply the model's central result: the allocation that maximises the instantaneous cross-section and the allocation that maximises the lifetime volume generally differ. Over-allocation raises the value at one instant while eroding subsequent states and pulling the horizon nearer; what is lost is not the share of a single day but the remainder of the interval.
Within this structure the Quantum Spacetime Strategy OS occupies a defined position. It does not set the objective, nor does it dictate the allocation. It supplies decision information that improves the choice of allocation, and it enters one domain — fortune — directly, by computing the three coordinates of person, time and space.
This paper describes a conceptual model and guarantees no particular outcome. Functional forms, boundary conditions and the design of measurement are positioned as subjects for future research.
For the Quantum Spacetime Strategy OS, see the canonical page.