Automated search for several alternative logical inferences in a mivar knowledge base

The complexity of the subject areas in which intelligent information systems operate is steadily increasing. The tasks set for such systems are increasingly aimed at automating and robotizing spheres of human activity. The solution of such problems requires adaptive and flexible methods capable of taking into account dynamic changes in the environment in real time. The mivar approach to creating intelligent decision-making systems allows working with adaptive discrete structures and provides methods for making management decisions based on adaptive active logical inference based on the knowledge base of mivar rules. The mivar machine of logical inference is the core of expert systems based on the mivar approach. As a result of the historical development of the mivar approach when working on different subject areas, various versions of mivar machines of logical inference with their algorithms for bypassing rules in the knowledge base were obtained. This paper discusses the reasons for the emergence of such options and demonstrates the need to use a parallel algorithm for activating rules in an adaptive network of logical rules when solving problems of action planning in technical systems.

Reasons for using parallel activation of logical rules in solving management tasks

Aladin,

Kotsenko,

Kim

et al. 2024

Methodology for automated assembly and delivery of products using mivar expert systems

Andreev,

Kotsenko,

Kim

et al. 2024

The paper presents an analysis of the task of automating assembly using robots with mivar decision-making systems. The question of the relevance of solving this problem is considered. The trend of robot development and their application in various sectors is also examined: from delivering parcels to customers to industrial warehouses. The use of mivar expert systems allows solving a large number of tasks for planning robot actions. Moreover, solving planning tasks allows us move towards a fully autonomous delivery transport system. The subject area and existing analogs are analyzed. The algorithm for implementing this task is described. In the end, a conclusion is given and the feasibility of this system is evaluated. This work describes part of the architecture of a web application, which is a cloud constructor of mivar expert systems. The created expert systems can have any subject area embedded in them by the architect. The main principles in development were: convenience, maintainability, scalability. Parameters necessary for the operation of expert systems were defined for further object representation: thing, property, relation. Based on the calculated parameters, expert systems make a decision about further actions. This work is intended for engineers involved in the development of autonomous robotic systems related to the delivery of goods.

Comparison of ChatGPT and Bard for using in hybrid intelligent information systems

Kim,

Kotsenko,

Andreev

et al. 2024

The purpose of this paper is to conduct research and comparative analysis of modern large language models, in particular, such as ChatGPT and Google Bard. As part of the research, the analysis of the advantages and disadvantages of advanced artificial intelligence technologies in various fields of application was carried out. Optimal conditions for using these models were identified, and methods for overcoming the identified shortcomings of large language models based on the mivar approach were proposed. Special attention is paid to the areas of application of large language models, such as providing a quick and effective response to user requests, as well as their use in training and staff adaptation tasks. This paper analyzes large language models, taking into account their integration methods, as well as the possibilities of creating personalized systems for automating communications. The research results include an analysis and comparison of the capabilities of LLM and identifying their advantages and disadvantages with a focus on the problem of “hallucinations”. The paper also proposes hypotheses about the potential overcoming of LLM limitations using the mivar approach. The results of experiments with ChatGPT confirm the relevance of creating structured knowledge and automating the process of building mivar data models, as well as indicate the prospects for combining LLM and the mivar approach. This can reduce the likelihood of generating erroneous information, increase the interpretability of results, and ensure more effective use of language models in various scenarios of artificial intelligence use.