THE SITUATION OF UNCERTAINTY THAT ARISES IN THE PROBLEMS OF SEMANTICS AND WAYS TO SOLVE IT

Various types of uncertainties that arise when solving semantics problems are considered. Decision theory investigates this situation involving incomplete input, current, and fuzzy information. But uncertainty in the problems of semantics has other manifestations. Its solution is carried out in different ways depending on its types. The problems of this class are related to recognition and when establishing the essence of certain objects, measures of similarity are introduced, which are a subjective assessment. For different measures, the values of the objective functions may differ due to the ambiguity of the result obtained for these functions or the chosen degree of similarity measures, and may not satisfy the purpose of the study. When choosing the result there is a situation of uncertainty. But with some measures of similarity, you can find a global solution. Such problems are divided into subclasses of solvable problems. Since the problems of semantics are reduced to combinatorial optimization problems, in which the argument of the objective function is combinatorial configurations, the situation of uncertainty may be related to the special structure of the set of combinatorial configurations. To solve it, it is necessary to enter several objective functions or to conduct optimization according to several criteria, which are reduced to a weighted criterion (linear convolution). Finding the optimal solution is carried out by self-tuning algorithms taking into account the constant and variable criteria, which are introduced in the process of solving the problem. That is, in the process of the algorithm generates additional current information (quality criteria), which affects the prediction of future results. The situation of uncertainty is manifested both due to developed fuzzy rules of information processing and evaluation and ambiguity in the choice of the optimal solution for several criteria in multicriteria optimization. To get out of this situation, self-tuning algorithms are developed, using the introduction of formal parameters in the process of solving the problem, which generates auxiliary current information that can not be specified in the input data. Also, subclasses of solvable problems are used to solve the situation of uncertainty, the reference library is structured to reduce unsolvable problems to solvable ones.

The subset sum game revisited

We discuss a game theoretic variant of the subset sum problem, in which two players compete for a common resource represented by a knapsack. Each player owns a private set of items, players pack items alternately, and each player either wants to maximize the total weight of his own items packed into the knapsack or to minimize the total weight of the items of the other player. We show that finding the best packing strategy against a hostile or a selfish adversary is PSPACE-complete, and that against these adversaries the optimal reachable item weight for a player cannot be approximated within any constant factor (unless P=NP). The game becomes easier when the adversary is short-sighted and plays greedily: finding the best packing strategy against a greedy adversary is NP-complete in the weak sense. This variant forms one of the rare examples of pseudo-polynomially solvable problems that have a PTAS, but do not allow an FPTAS (unless P=NP).

Construction of potential functions associated with a given energy spectrum — An inverse problem II

We continue our solution of the inverse problem started by the first author in [Int. J. Mod. Phys. A 35, 2050104 (2020)]. Additional potential functions for exactly solvable problems that correspond to the same energy spectrum formula but for different energy polynomials and bases are found. In this work, we obtain a class of potential functions associated with the Wilson polynomial and “Jacobi basis.”

Medical disposals and problem solving: About high blood pressure in Morocco

In this article, I analyze how in basic health-care facilities in Morocco, general practitioners transform patients’ problems into solvable problems, taking into account constraints related to medical standards, financial issues, the organization of the health system, and care. My focus is on hypertension, or high blood pressure. I argue that standards allow the solving of patients’ problems through the production of an entity called high blood pressure. However, the ‘high blood pressure’ enacted is different from the entity defined by standards. Fragments of the latter, borrowed from other contexts, are put to work in Morocco, while the material arrangements needed to enforce and have them work without discontinuities do not exist. This contributes to the production of an entity configured at a moment in time between standards and patients’ lives.

Construction of potential functions associated with a given energy spectrum — An inverse problem

Using a formulation of quantum mechanics based on orthogonal polynomials in the energy and physical parameters, we present a method that gives the class of potential functions for exactly solvable problems corresponding to a given energy spectrum. In this work, we study the class of problems associated with the continuous dual Hahn polynomial. These include the one-dimensional logarithmic potential and the three-dimensional Coulomb plus linear potential.

PList-based Divide and Conquer Parallel Programming

This paper details an extension of a Java parallel programming framework – JPLF. The JPLF framework is a programming framework that helps programmers build parallel programs using existing building blocks. The framework is based on {\em PowerLists} and PList Theories and it naturally supports multi-way Divide and Conquer. By using this framework, the programmer is exempted from dealing with all the complexities of writing parallel programs from scratch. This extension to the JPLF framework adds PLists support to the framework and so, it enlarges the applicability of the framework to a larger set of parallel solvable problems. Using this extension, we may apply more flexible data division strategies. In addition, the length of the input lists no longer has to be a power of two – as required by the PowerLists theory. In this paper we unveil new applications that emphasize the new class of computations that can be executed within the JPLF framework. We also give a detailed description of the data structures and functions involved in the PLists extension of the JPLF, and extended performance experiments are described and analyzed.

Asymptotically Unambitious Artificial General Intelligence

General intelligence, the ability to solve arbitrary solvable problems, is supposed by many to be artificially constructible. Narrow intelligence, the ability to solve a given particularly difficult problem, has seen impressive recent development. Notable examples include self-driving cars, Go engines, image classifiers, and translators. Artificial General Intelligence (AGI) presents dangers that narrow intelligence does not: if something smarter than us across every domain were indifferent to our concerns, it would be an existential threat to humanity, just as we threaten many species despite no ill will. Even the theory of how to maintain the alignment of an AGI's goals with our own has proven highly elusive. We present the first algorithm we are aware of for asymptotically unambitious AGI, where “unambitiousness” includes not seeking arbitrary power. Thus, we identify an exception to the Instrumental Convergence Thesis, which is roughly that by default, an AGI would seek power, including over us.