Zagadnienie skuteczności pomocy społecznej. Symboliczna (oczekiwana) tożsamość klienta pomocy społecznej. Pomoc społeczna jako gra o kontrolę sfer niepewności. (Raport z badań)

The article pertain to a case study research of social assistance processes in a social policy system of G. city. A main method of investigation was opened, unstandardized systematic interviews with social workers, political figures and administrators of the system. Social services in experiences of our respondents we have interpreted as games for uncertainty control. The games in perspectives of social workers and administrators of the system we understand as pedagogical environments for customers which in the processes of these interactional games shape many of the social, adaptive skills. Such skills enable customers institutional identity management and effective winning spheres of freedom from control. Behavioural strategies of social workers in institutional and organizational environment in relation to customers we conceptualize as exchange models of a “gift for power” above customers spheres of uncertainty control. Inefficiency of social assistance comes from incapacity of such aid to effectively exchange gifts for uncertainty control in daily situations for customers. The Institution of social services has many functional substitutes in social, political and economic environments which are much more effective. Second goal of our investigation was a presentation and portrayal of the real pedagogical environment of social workers. Theory of social intervention and social pedagogy suffers from too many abstracts from reality foundations, premises und presumptions. So social pedagogy as practical science needs also careful and diligent investigation of real social practices in institutional and organizational environment of social policy systems.

A Survey on Novel Estimation Approach of Motion Controllers for Self-Driving Cars

The motion planning framework is one of the challenging tasks in autonomous driving cars. During motion planning, predicting of trajectory is computed by Gaussian propagation. Recently, the localization uncertainty control will be estimating by Gaussian framework. This estimation suffers from real time constraint distribution for (Global Positioning System) GPS error. In this research article compared novel motion planning methods and concluding the suitable estimating algorithm depends on the two different real time traffic conditions. One is the realistic unusual traffic and complex target is another one. The real time platform is used to measure the several estimation methods for motion planning. Our research article is that comparing novel estimation methods in two different real time environments and an identifying better estimation method for that. Our suggesting idea is that the autonomous vehicle uncertainty control is estimating by modified version of action based coarse trajectory planning. Our suggesting framework permits the planner to avoid complex and unusual traffic (uncertainty condition) efficiently. Our proposed case studies offer to choose effectiveness framework for complex mode of surrounding environment.

Uncertainty Control Strategies in Solving of Prognostic Tasks

The aim of the article was to study the role of personality and intelligence in prognostic tasks solving. The presented results were obtained in a sample of 78 participants. Seven methods were used: a computerized version of the prognostic task (based on V.N. Azarov`s task [1982]; an intelligence test and five psychodiagnostic questionnaires to assess personality traits and style characteristics. In the prognostic task, three measurable indicators of the possible strategy were considered: the ratio of available and missing information (awareness), the reasonableness of the possible choice by the available amount of the information (justifiability) and the change in the prognosis reasonableness due to the latest obtained information (trend). The correlations between intelligence measurement and preferred levels of awareness (r = 0.261, p <0.05) and validity (r = 0.244, p <0.05) were established. Two strategies of uncertainty control, differing by the use of the above-mentioned indicators were identified and described with the awareness-only oriented strategy seeming more successful. There were differences in the intolerance of uncertainty levels (measured by the New Questionnaire of Tolerance/Intolerance for Uncertainty by T.V. Kornilova [11]) in the individuals who preferred different strategies of uncertainty control (U = 558, p = 0.047). The participants who tried to use all the three indicators in solving the prognostic task were more uncertainty intolerant than the awareness-only oriented group.

A Strategy for the Control of Uncertainty and WIP

High works-in-process (WIP) levels usually involve significant losses for companies as they trigger dispatching delays, product shortages, increases in immobilized capital, and greater storage costs, among others. This study provides a strategy for gradually decreasing the WIP levels associated with the production line of a pharmaceutical company located in Latin America. The methodology used is based on Lean practices and, more specifically, organized into phases: the diagnosis of the current situation, information processing, mapping out the current situation through value stream mapping, analysis and determination of key factors for uncertainty control, and improvement proposals. The main tools used are value stream mapping, 5-whys, single-minute exchange of dies, and total productive manufacturing.

Heuristic Sensing: An Uncertainty Exploration Method in Imperfect Information Games

Imperfect information games have served as benchmarks and milestones in fields of artificial intelligence (AI) and game theory for decades. Sensing and exploiting information to effectively describe the game environment is of critical importance for game solving, besides computing or approximating an optimal strategy. Reconnaissance blind chess (RBC), a new variant of chess, is a quintessential game of imperfect information where the player’s actions are definitely unobserved by the opponent. This characteristic of RBC exponentially expands the scale of the information set and extremely invokes uncertainty of the game environment. In this paper, we introduce a novel sense method, Heuristic Search of Uncertainty Control (HSUC), to significantly reduce the uncertainty of real-time information set. The key idea of HSUC is to consider the whole uncertainty of the environment rather than predicting the opponents’ strategy. Furthermore, we realize a practical framework for RBC game that incorporates our HSUC method with Monte Carlo Tree Search (MCTS). In the experiments, HSUC has shown better effectiveness and robustness than comparison opponents in information sensing. It is worth mentioning that our RBC game agent has won the first place in terms of uncertainty management in NeurIPS 2019 RBC tournament.

Ensuring Reliability of Control Data in Engineering Systems

The paper presents the approach of determination of rationality coefficients of control system, inputted uncertainty, control of the process, system errors, and uncertainty. Algorithms for identifying the states of system have been developed on the basis of theorems of identification. They actually implement the theoretical multiplication cross-section and establish that increasing the reliability of information is possible only through the use of redundancy (structural, procedural, and informational). The increase in the reliability of control data with the developed methods ensures significant improvement of the functioning of information systems and facilitates the adoption of more substantiated decision making.

Computer-Based Prognostic Task Measurements as Indicators of Uncertainty Acceptance

There were few studies of individual differences in prognostic decision-making from the psychological point of view; most of them focused on the differences between novices and experts making the prognoses. In this study, we suggested a new task that matched the criteria of a prognostic one, was computerized, and did not require expertise in any field of knowledge. Thus, the proposed method investigated how people processed information and controlled uncertainty in prognostic tasks. On a sample of 78 people aged 17–66, we used a quasi-experimental design to find the patterns of the proposed task parameters and how they correlated with personality and cognitive variables. Five well-known personality questionnaires accessing traits, known to be included in decision-making regulation, were used along with a cognitive abilities test to measure those variables. Two patterns were identified via cluster analysis. Differences in intolerance for uncertainty were demonstrated for the people from two identified clusters. Those patterns could be interpreted as uncertainty control strategies for decision-making grounding in prognostic tasks.