scholarly journals Forms of thinking of autonomous intelligent agents: Features and problems of their organization

2020 ◽  
pp. 224-230
Author(s):  
В.Б. Мелехин ◽  
М.В. Хачумов
Keyword(s):  
Knowledge Representation ◽  
Intelligent Agents ◽  
A Priori ◽  
Current Situation ◽  
Conceptual Thinking ◽  
Representation Model ◽  
Living Organisms ◽  
Figurative Thinking ◽  
Thinking Tools ◽  
Functional Purpose

Обосновано, что по аналогии с живыми организмами, для решения в проблемной среде различных по сложности задач, автономных интеллектуальных агентов различного назначения целесообразно наделить тремя дополняющими друг друга следующими формами мышления: наглядно-действенного, наглядно-образного и понятийного мышления. Определено функциональное назначение каждого отмеченного выше вида мышления. В частности показано, что наглядно-действенное мышление позволяет автономным интеллектуальным агентам эффективным образом целенаправленно функционировать и изучать закономерности преобразования текущей ситуации априори неописанной проблемной среды. Инструментальные средства наглядно-образного мышления предназначены для вывода решений в процессе планирования поведения связанного с целенаправленным преобразованием текущей ситуации проблемной среды на основе заданной модели представления знаний и процедур вывода решений. Понятийное мышление служит для пополнения недостающих знаний в процессе планирования поведения в недоопределенных условиях функционирования и для решения сложных задач поведения, требующих смены ситуаций проблемной среды для достижения заданной цели. Обозначены основные подходы, особенности и проблемы связанные с организацией инструментальных средств вывода решений в процессе планирования поведения автономных интеллектуальных агентов на основе рассмотренных видов мышления. It is substantiated that, by analogy with living organisms, in order to solve in a problem environment of various complexity tasks of autonomous intelligent agents for various purposes, it is advisable to endow with three complementary forms of thinking: visual-effective, visual-figurative and conceptual thinking. The functional purpose of each type of thinking noted above has been determined. In particular, it is shown that visual-active thinking allows autonomous intellectual agents to function efficiently and purposefully and study the laws of transformation of the current situation of an a priori undescribed problem environment. Visual-figurative thinking tools are designed to output decisions in the process of planning behavior associated with a targeted transformation of the current situation of the problem environment based on a given knowledge representation model and decision inference procedures. Conceptual thinking serves to replenish the missing knowledge in the process of planning behavior in underdetermined conditions of functioning and to solve complex problems of behavior that require a change in situations of the problem environment to achieve a given goal. The main approaches, features and problems associated with the organization of tools for deriving solutions in the process of planning the behavior of autonomous intelligent agents based on the considered types of thinking are outlined.

scholarly journals Polyvariable conditionally dependent predicates in the knowledge representation model of autonomous mobile intelligent agents

2021 ◽  
pp. 184-190
Author(s):  
В.Б. Мелехин ◽  
М.В. Хачумов
Keyword(s):  
Knowledge Representation ◽  
Intelligent Agents ◽  
A Priori ◽  
Subject Area ◽  
Problem Solver ◽  
Representation Model ◽  
Purposeful Behavior ◽  
Automatic Planning ◽  
Mental Acts ◽  
Further Development

Показано, что известные модели представления и обработки знаний не позволяют построить интеллектуальный решатель задач автономных мобильных интеллектуальных агентов, способных выполнять сложные задания в априори неописанных нестабильных условиях проблемной среды. Для решения данной актуальной проблемы в статье предлагаются типовые конструкции модели представления знаний безотносительно к конкретной предметной области, строящиеся на основе полипеременных условно-зависимых предикатов. Приведена структура данного вида предикатов и определены условия, при выполнении которых, в результате означивания входящих в них различного сорта переменных, получаются истинные высказывания, характеризующие необходимые условия для достижения стоящих подцелей и целей поведения в текущей ситуации нестабильной проблемной среды. Разработаны различные по назначению типовые элементы модели представления знаний автономных интеллектуальных агентов, позволяющие формировать на их основе различные по сложности программы целенаправленной деятельности связанные с выполнением сформулированного им задания. Отмечено, что дальнейшее развитие полученных в настоящей работе результатов связано с формализацией мыслительных актов и разработкой инструментальных средств обработки знаний для построения алгоритмов автоматического планирования целенаправленного поведения автономных мобильных интеллектуальных агентов в нестабильных недоопределенных условиях функционирования. It is shown that the known models of knowledge representation and processing do not allow constructing an intelligent problem solver for autonomous mobile intelligent agents capable of performing complex tasks in a priori undescribed unstable conditions of a problematic environment. To solve this topical problem, the article proposes standard constructions of a knowledge representation model, without reference to a specific subject area, based on polyvariable conditionally dependent predicates. The structure of this type of predicates is given and the conditions are determined under which, as a result of the valuation of variables included in them, true statements are obtained that characterize the necessary conditions for achieving behavioral sub goals and goals in the current situation of an unstable problematic environment. The standard and different in purpose elements of knowledge representation model for autonomous intelligent agents have been developed, which make it possible to form programs of purposeful activity of different complexity associated with the implementation of the formulated task. It is noted that further development of the results obtained in this work is associated with the formalization of mental acts and the development of knowledge processing tools for constructing automatic planning algorithms of the purposeful behavior of autonomous mobile intelligent agents in unstable underdetermined conditions.

Elements of Conceptual Thinking in Planning the Behavior of Autonomous Intelligent Agents

2021 ◽  
Vol 22 (8) ◽  
pp. 411-419
Author(s):  
V. B. Melekhin ◽  
M. V. Khachumov
Keyword(s):  
Intelligent Agents ◽  
Autonomous Agents ◽  
Initial Level ◽  
A Priori ◽  
Minimum Length ◽  
Special Role ◽  
Conceptual Thinking ◽  
A Priori Uncertainty ◽  
Mental Acts

The expediency of using the tools of visual-effective, visual-figurative and conceptual thinking for planning the purposeful activity of autonomous intelligent agents in problem environments of various degrees of a priori uncertainty has been substantiated. The content is revealed and the role of each form of thinking is shown in the process of automatic planning of the purposeful behavior of autonomous intelligent agents in the changing conditions of functioning. The special role of conceptual thinking in the performance of complex tasks by autonomous agents and the planning of polyphasic behavior associated with it is indicated. Taking into account the complexity of the problems associated with the formalization of mental acts of conceptual thinking, possible ways of its gradual development from the initial level to the transition to higher levels of development are shown, expanding on this basis the class of tasks solved by autonomous intelligent agents. A model of knowledge representation and tools for deriving solutions of the initial level of conceptual thinking have been developed, which allow intelligent agents to break down the tasks they receive into sub-goals of behavior. Then, on this basis, plan polyphase activity by searching for solutions to the associated subtasks, which ensure the determination of the minimum length routes of movement in a prob lematic environment with obstacles and the purposeful manipulation of objects in it. The tools are synthesized allowing to establish the order of elaboration of complex actions included in the structure of the task formulated by autonomous intelligent agents. It is shown that the further development of the proposed methodological foundations for constructing intelligent problem sol vers is associated with the formalization of a higher level of mental acts of conceptual thinking, which make it possible to solve practical problems of different complexity, formulated both in procedural and declarative form of presentation in the form of various target situations of the problem environment, having a large dimension.

Instrumental Means for Managing the Rational Behavior of Self-Organizing Autonomous Intelligent Agents

2021 ◽  
Vol 22 (4) ◽  
pp. 171-180
Author(s):  
V. B. Melekhin ◽  
M. V. Khachumov
Keyword(s):  
Intelligent Agents ◽  
Environmental Changes ◽  
A Priori ◽  
Operating Conditions ◽  
Basic Principles ◽  
Purposeful Behavior ◽  
Problem Solvers ◽  
Boundary Estimates ◽  
Self Learning ◽  
Self Organizing

We formulate the basic principles of constructing a sign-signal control for the expedient behavior of autonomous intelligent agents in a priori undescribed conditions of a problematic environment. We clarify the concept of a self-organizing autonomous intelligent agent as a system capable of automatic goal-setting when a certain type of conditional and unconditional signal — signs appears in a problem environment. The procedures for planning the expedient behavior of autonomous intelligent agents have been developed, that imitate trial actions under uncertainty in the process of studying the regularities of transforming situations in a problem environment, which allows avoiding environmental changes in the process of self-learning that are not related to the achievement of a given goal. Boundary estimates of the proposed procedures complexity for planning expedient behavior are determined, confirming the possibility of their effective implementation on the on-board computer of the automatic control system for the expedient activity of autonomous intelligent agents. We carry out an imitation on a personal computer of the proposed procedures for planning purposeful behavior, confirming the effectiveness of their use to build intelligent problem solvers for autonomous intelligent agents in order to endow them with the ability to adapt to a priori undescribed operating conditions. The main types of connections between various conditional and unconditional signal — signs of a problem environment are structured, which allows autonomous intelligent agents to adapt to complex a priori undescribed and unstable conditions of functioning.

A Hypergraph-Based Knowledge Representation Model for Smart Product-Service System Development

2021 ◽  
Author(s):  
Wang Zuoxu ◽  
Li Xinyu ◽  
Chen Chun-Hsien ◽  
Zheng Pai
Keyword(s):  
Knowledge Representation ◽  
Domain Knowledge ◽  
Manufacturing Companies ◽  
Binary Relations ◽  
Fundamental Study ◽  
Essential Information ◽  
Knowledge Reasoning ◽  
Representation Model ◽  
Product Service ◽  
Smart Product

Abstract In the trend of digital servitization, manufacturing companies have been transforming their business paradigms to Smart product-service systems (Smart PSS) by integrating products and associated services as bundles. To support the knowledge-intensive process of Smart PSS development, massive domain knowledge should be well-organized and reused. However, due to the existence of non-binary relations caused by product-service bundles (PSB) and context-awareness concerns in the Smart PSS development activities, conventional graph-based approaches for knowledge representation may lose essential information in transforming non-binary relations into binary ones, and hence cause incorrect results in the subsequent knowledge queries. To mitigate this problem, a hypergraph-based knowledge representation model for Smart PSS was proposed, which represents the non-binary relations among multiple entities with hyperedges. Technically, the knowledge source and the typical hyperedge schema in Smart PSS development are identified in this paper. A detailed case study in the scenarios of 3D printing troubleshooting and PSB recommendation was conducted to showcase the proposed hypergraph-based knowledge representation model and demonstrate its validity. The results show that the hypergraph-based knowledge model significantly relieves the sparsity in the ordinary KG by adding multiple hyperedges. It is anticipated that the proposed hypergraph knowledge representation model can serve as a fundamental study for further knowledge reasoning activities.

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