Kitabı oxu: «TSFK: Life, the Universe, and Everything»

© Vladimir Sayapin, 2026

ISBN 978-5-0071-4643-2

Created with Ridero smart publishing system

Vladimir Sayapin

TSFK: Life, the Universe, and Everything

2026

Introduction

Human beings make decisions under incomplete knowledge. No choice exists independently of some representation of the situation, its causes, and its possible consequences. The fewer known relationships there are between phenomena, the more assumptions a decision contains, and the higher the probability of error.

This problem is not eliminated by accumulating individual facts. Even a substantial amount of knowledge does not mean knowing all the relevant relationships between known and unknown phenomena. Therefore, until finite knowledge is reached, every decision remains a decision made under conditions of uncertainty.

This gives rise to a fundamental question: how should an intelligence act if it is forced to make decisions without possessing complete knowledge of their consequences?

The Theory of the Search for Finite Knowledge proceeds from the premise that the ultimate task of cognition is to reach a state in which the unknown no longer limits the ability to draw justified conclusions about reality. In a finite system, this may mean exhaustive knowledge. In an infinite system, finite knowledge may be represented by a finite set of principles that makes it possible to determine its structure at any level.

Until this state is reached, intelligence has no basis for absolute certainty. Therefore, it must act while simultaneously preserving the possibility of correcting its own errors. From this follows the principle of reversibility of consequences: under insufficient knowledge, decisions that minimize irreversible harm and preserve future possibilities for changing the decision should be preferred.

However, reversibility alone is insufficient for comparing incompatible actions. For this, it is necessary to take into account the probabilistic structure of the future: possible events, their probabilities, potential consequences, the cost of error, the stability of the result, and the possibility of further accumulation of effects. This gives rise to the problem of rationally comparing future states under incomplete knowledge.

This work examines, in sequence, the limits of knowledge, the necessity of acting before it is reached, the principle of reversibility of consequences, the concept of potential, and the mechanism of rational choice. It then derives the search for finite knowledge as a systemic goal from these propositions and examines the implications of the theory for autonomous strong artificial intelligence.

The main task of this work is not to describe desirable behavior, but to derive it from the limitations of knowledge.

Part I. The Limits of Knowledge

Chapter 1. Decision and Knowledge

Any decision constitutes a choice between possible actions. A choice is determined by a representation of the current state of a system and of the consequences of the available actions. Therefore, a decision depends on knowledge of the situation itself and of its relationships with other phenomena.

If all relevant relationships between an action and its consequences are known, the choice may be justified. If some of these relationships are unknown, the consequences have to be assumed. The greater the number of relevant unknowns, the greater the uncertainty of the result.

This can be represented as follows: an action (A) has a set of possible consequences (C_1, C_2, …, C_n). With complete knowledge of the system of relationships between (A) and (C_i), the choice is determined by the known consequences. With incomplete knowledge, part of the set of consequences or the relationships to them is unknown, and therefore the decision contains an element of assumption.

Consequently, the degree to which a decision is justified is limited by the degree of knowledge on which it is based. It is impossible to obtain a reliable conclusion about the unknown solely from the known if the necessary relationship between them has not been established.

This does not mean that incomplete knowledge makes a decision impossible. It means that every decision made before the relevant uncertainty has been eliminated contains a probability of error.

The following question arises: is there a limit beyond which uncertainty can in principle be eliminated?

Chapter 2. Finiteness and Infinity of Knowledge

The amount of possible knowledge is determined by the structure of the reality that must be known. If the totality of what exists has a finite structure and a finite number of fundamentally distinguishable states, then an exhaustive description of this totality can, in principle, also be finite.

If reality is infinite, however, this does not imply the impossibility of finite knowledge. An infinite object can be specified by a finite principle that determines its structure at any scale. In such a case, describing the object does not require enumerating an infinite number of states.

Therefore, it is necessary to distinguish between the amount of what is being described and the amount of the principle sufficient to describe it. The infinity of the former does not imply the infinity of the latter.

Thus, there are two fundamental cases.

In the first case, finite knowledge may constitute exhaustive knowledge of a finite reality.

In the second case, finite knowledge may constitute a finite system of principles from which the properties of an infinite reality follow.

Consequently, the question of the finiteness of knowledge cannot be reduced to the question of whether the Universe is finite. In both cases, a state is logically possible in which the unknown ceases to be a fundamental obstacle to inference.

This state will henceforth be called finite knowledge.