=Paper=
{{Paper
|id=Vol-2870/paper81
|storemode=property
|title=The Ontological Decision Support System Composition and Structure Determination for Commanders of Land Forces Formations and Units in Ukrainian Armed Force
|pdfUrl=https://ceur-ws.org/Vol-2870/paper81.pdf
|volume=Vol-2870
|authors=Olesya Pashchetnyk,Vasyl Lytvyn,Vyacheslav Zhyvchuk,Leonid Polishchuk,Victoria Vysotska,Zoriana Rybchak,Yulia Pukach
|dblpUrl=https://dblp.org/rec/conf/colins/PashchetnykLZPV21
}}
==The Ontological Decision Support System Composition and Structure Determination for Commanders of Land Forces Formations and Units in Ukrainian Armed Force==
https://ceur-ws.org/Vol-2870/paper81.pdf
The Ontological Decision Support System Composition and
Structure Determination for Commanders of Land Forces
Formations and Units in Ukrainian Armed Forces
Olesya Pashchetnyka, Vasyl Lytvynb, Vyacheslav Zhyvchuka, Leonid Polishchuka, Victoria
Vysotskab, Zoriana Rybchakb, Yulia Pukachb
a
Hetman Petro Sahaidachnyi National Army Academy, Heroes of Maidan Street, 32, Lviv, 79012, Ukraine
b
Lviv Polytechnic National University, S. Bandera street, 12, Lviv, 79013, Ukraine
Abstract
The subject of the article is the ontological decision support system in automated military
control systems. The primary purpose of the work is to determine the composition and structure
of the decision support system by commanders of formations and units of the Land Forces of
the Ukrainian Armed Forces using an ontological approach. The objective is development:
A decision support system based on the ontological knowledge base;
A prototype of software, mathematics and information support for it;
Offers for an algorithm of functional activities of the Land Forces of the Ukrainian Armed
Forces from the battalion and above according to US Armed Forces standards (MDMP) at
each stage (steps) of the military decision-making process.
The essential features of the decision support system for commanders of formations and units
of the Land Forces of the Armed Forces of Ukraine is a central component of an ontological
knowledge base. Described the possible use of ontologies to represent structured constituent
decision-making and related components domains that describe this process. The subject area
ontology built to describe and explain the decision-making process of MDMP according to the
standards of NATO member countries based on knowledge formalised in guiding documents
for information exchange, database structure, and software implementation of models, methods
and algorithms of individual modules of the decision support system. A prototype software and
mathematics and information management are developed, which can be used as a prototype for
future automated subsystem management of the Land Forces of the Armed Forces of Ukraine.
It is for simulating the formation and ontological decision support system for commanders of
buildings and units of the Land Forces of the Armed Forces of Ukraine. According to the US
Armed Forces (MDMP) standards, the work of officials' work algorithm of the battalion and
above is proposed. Automation of each stage (step) of MDMP gives the chance to reduce the
time for decision-making. The algorithm can be used to implement the educational process of
training officers and cadets of higher military educational establishments in the centre of
simulation and subsequently for use in decision-making in warfare and the army training
centres.
Keywords 1
Decision support system, ontology, knowledge base, software-mathematical and information
support, decision making, armed force, land force, decision making process, subject area,
military decision making process, decision support, military decision making, intelligent
system, ontological decision support system, NATO member country, making process
according, combat mission, combat operation, NATO standard, information support, multi
agent system, Ukrainian armed force, automated control system, intelligent decision support
system, information exchange, game method
COLINS-2021: 5th International Conference on Computational Linguistics and Intelligent Systems, April 22–23, 2021, Kharkiv, Ukraine
EMAIL: Olesyalviv@i.ua (O. Pashchetnyk); vasyl.v.lytvyn@lpnu.ua (V. Lytvyn); lev-sl@ukr.net (V. Zhyvchuk); Polischyk_LI@i.ua (L.
Polishchuk); victoria.a.vysotska@lpnu.ua (V. Vysotska); zozylka3@gmail.com (Z. Rybchak); ilpach@yahoo.com.ua (Y. Pukach)
ORCID: 0000-0001-8726-1112 (O. Pashchetnyk); 0000-0002-9676-0180 (V. Lytvyn); 0000-0001-6980-9914 (V. Zhyvchuk); 0000-0002-
4379-3990 (L. Polishchuk); 0000-0001-6417-3689 (V. Vysotska); 0000-0002-5986-4618 (Z. Rybchak); 0000-0002-6358-8396 (Y. Pukach)
©️ 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
1. Introduction
The trend towards creating automated control systems (ACS) for the army and weapons is to
integrate intelligence, communications, automation, geographic information systems (GIS) and
navigation, combat destruction, and comprehensive support. Functionally, this means combining into a
single system of the above subsystems, which should include a subsystem for decision support - the
algorithm of management, special software, automated methods of information processing, situation
assessment, preparation of management decisions with the choice in the process of comparing the most
effective of them [1].
However, the implementation of the decision support system (DSS) as a component of the ACS of
the Land Forces (LF) of the Armed Forces (AF) of Ukraine, which has not yet been established, with
the gradual increase of its capabilities, is a complex scientific and technical problem. The difficulties
that commanders have in making decisions and planning in conditions of the conduct of hostilities are:
The presence of uncertain factors and insufficient knowledge about values of the characteristics
of objects in critical situations, about the goals, algorithm and management resources;
The need to analyse a large amount of information with the existing shortage of time spend on
working off combat documents, bringing tasks (commands, signals, orders) to subordinates, etc.
[2].
New methods/algorithms Improvement and development for commanding bodies actions in the
Ukrainian Armed Forces LF from the battalion and above should be supported by relevant information
and basic knowledge. It is in the field of facility management, taking into account the US Armed Forces
standards (MDMP - Military Decision - Making process), which are identical to NATO standards (OPP
[3-19]. The knowledge base created based on the ontological approach will provide at each step of the
process military decision-making to apply methods and algorithms for finding solutions and models
and methods of optimisation and data mining presented in it. [20]. Therefore, rational presentation of
knowledge about the tasks and the decision-making process is one of the main problems of building
any intelligent system. In addition, an important task is the composition and structure development for
ontological DSS commanders of Ukrainian Armed Forces formations and units at Land Forces.
2. Recent research and publications analysis
The scientific and technical literature does not pay enough attention to the development of
methodological aspects related to the construction of specific ontologies for DSS of combat operations
and their management, taking into account the standards of NATO member countries. Still, several
scientific studies emphasise the relevance of this topic.
The article [21] presents the ontology of the field of knowledge "Support for decision-making in
poorly structured areas". The author considered this ontology as a conceptual basis of an intellectual,
scientific Internet resource, which contains systematised information about this area of knowledge,
presents meaningful access to information, processing and solving typical problems. The article shows
that the field of learning described by ontology extends the classical theory of decision-making. Still,
the theoretical knowledge of the subject area is not enough to work off methodological aspects related
to the construction of specific ontologies for DSS of governing bodies.
The integration of various information resources in the management system of military technologies
in [22] is based on the procedures of transdisciplinary ontologies. An approach to the construction of
an information-analytical system (IAS) is proposed, which provides the solution of cognitive meta-
tasks: "structuring", "analysis", "synthesis", "rational choice" in the processing of text documents,
databases and knowledge bases. This approach advantage is the IAS focuses on processing large
amounts of unstructured and spatially distributed information. In addition, it is built as a modern
management system of network information arrays of different size and knowledge systems based on
ontological management and analytical component, creating a functional model. However, the solutions
implemented by the author do not allow to entirely building an effective decision support system in the
field of technology management for military purpose.
The article [23] considers the main provisions of the ontological approach to integrating
heterogeneous information resources underlying the information interaction of heterogeneous
automated special-purpose systems. It proposes the ontological approach to combining heterogeneous
computerised techniques based on a hybrid method of ontology interaction. As for the disadvantages of
this method, it is worth noting the lower performance of calculations on ontologies compared to
relational database management systems. This circumstance can lead to negative consequences, which
can be expressed in the violation of semantic connections of concepts and classes. Thus, it will allow
considering the ontological model of the description of the subject area of the information task
inadequate.
3. The article purpose formulation
The purpose of the article is to determine the composition and structure of the decision support
system by commanders of compounds and units of the Land Forces of the Ukrainian Armed Forces
based on structuring the characteristic features of knowledge. One of the means of implementing such
an approach to the presentation of knowledge is the ontological approach. Therefore, it is necessary to
develop a prototype of the software, mathematics and information support for the functioning of
ontological DSS with proposals for the algorithm of functional activities of governing bodies of the LF
Ukrainian Armed Forces from the battalion and above by the standards of the US Armed Forces
(MDMP) at each stage (steps) of the process military decision-making.
4. Presenting main material
Ordering and effective use of the necessary information for the preparation and conduct of hostilities
by commanders of formations and units of the LF of the AF of Ukraine is possible under conditions of
building an ontology of military decision-making, orderly and structured knowledge using specific
conceptualisation. Conceptualisation involves the description of many objects and concepts, learning
about them and the relationship between them. Today, the task of forming conceptual "transparent"
representations for weakly structured subject areas (SA), which are characterised by the lack of strict
mathematical models, is relevant. The leading paradigm of structuring information flows are ontologies
- knowledge, formally reflected based on conceptualisation or hierarchical conceptual structures formed
by the analyst based on the study and structuring of information flows, documents, knowledge protocols
and other sources [24-25]. There are three types of ontologies [26]:
1. Domain-oriented. The SA ontology contains concepts taxonomy, other relations, instances of
classes and various types of constraints (axioms). Axioms set semantic rules for the system of
relations.
2. Task-oriented. Describe the solution of specific problems, the source of knowledge of the
specifications of structures (databases) and data processing methods.
3. Top-level. The general ontology describes the categories - the concept of the upper level.
Examples are physical, functional, behavioural concepts and relationships that relate to general
scientific concepts and relationships.
Recently, it has accepted to build a single ontology, which contains three types of ontologies.
Hierarchically, it looks like this: the general ontology is at the top of the hierarchy, and the ontologies
of the subject area and tasks are connected to it. This approach allows you to consider all the functions
within the subject area holistically and the knowledge described in the ontology - to use in other
programs, databases, etc. Significantly increases the efficiency of intelligent decision support systems.
The set of axioms (constraints) that make up the ontology has a first-order logic theory. The dictionary
terms are the names of unary and binary predicates, called concepts and relations, respectively. In the
simplest case, an ontology describes only a hierarchy of concepts related to inheritance and aggregation.
In addition, appropriate axioms are added to express other relationships between concepts and to limit
their interpretation. Given the above, the ontology is a simplified basic model (base) for the organisation
of knowledge storage, which describes the facts that are always true within a particular community
based on the generally accepted meaning of the dictionary used.
Usually, the formal model scheme for ontology O by three of this kind is described [27-33]:
O C, R, F , (1)
where C is a finite set of concepts (concepts, terms) of the subject area, which is set by the ontology O;
R is a finite set of relations between concepts (concepts, terms) of a given subject area;
F is a finite set of interpretation functions (axiomatization, constraints) given on ontology
concepts or relations O.
In general, the structure of the ontology is a set of elements of four categories [34]:
1. Concepts (classes, concepts, categories). They are considered conceptualisations of all
representatives of an entity or phenomenon. In addition, they are general categories that can be
arranged hierarchically [35-37]. Each class describes a group of individual entities that are
combined based on the presence of common properties. They can store all concepts (types,
concepts, categories) in the knowledge base in open and extended form can be stored, both
formalised or not.
2. Relation. Represent the type of interaction between the concepts of the subject area, connect the
classes, and describe them [38-41]. The most common type of relation used in all ontologies is
the categorisation relation, i.e., assigning an object to a specific category.
3. Axioms. They set the conditions for the correlation of categories and relations; they express
obvious statements that connect concepts and references [42-47]. Allow communicating the
information that cannot be expressed in the ontology by building a hierarchy of concepts and
establishing different ideas. Hypotheses can be included in an ontology for various purposes: to
verify information's correctness, derive new information, or define complex constraints.
4. Instances (individuals). Individual representatives of a class of entities or phenomena, i.e.
specific elements of a particular category [48-52].
Thus, the components of the ontology are subject to a kind of hierarchy. At the lower level of this
hierarchy are specific individuals; higher are the concepts, i.e. categories. At a higher level are the
relationships between these concepts [53]. Rules and axioms unite all these elements.
Within the proposed subject area MDMP, a prototype of software-mathematical and information
support (SMaIS) was developed, which is the basis for the development of ontological DSS of
commanders of formations and units of the LF of the AF of Ukraine (Fig. 1) [54].
When creating SMaIS ontological DSS, it is proposed to use a modular approach, which allows
developing basic modules. The model's functionality is divided into modules, the expansion of the
functionality of which occurs by adding a new module to the system. According to NATO standards,
the module "Military decision-making process" is built using an ontological approach, a functional
addition through the addition of new stages in which will adapt the core of the ontological model to a
specific subject area. The basis for the formation of such DSS is the formalisation of algorithms (order)
of work of commanders, namely the process of military decision-making MDMP, for which the
program is formed a hierarchical structure. The upper level of this structure includes the known seven
stages (steps) of the MDMP decision-making process (first level of the hierarchy), with the
corresponding sub-stages (second level of the order), the tasks performed in these sub-stages (third level
of the scale), and the actions of commanders (fourth level hierarchy) (Fig. 1).
Among the stages of MDMP, the top level of the hierarchy of algorithms are as follows:
Obtaining a combat mission;
Analysis of the combat mission;
Development of probable options for combat operations;
Analysis of possible options for action and conducting a war game;
Comparison of possible options for action;
Choice of action option and its approval;
Issuance of plans and orders.
The specified hierarchical structure that in detail defines algorithms of work of commanders at
decision-making on conducting military operations is supplemented with additional functionality,
namely:
Information and information-calculation tasks for:
a. The organisation of management, interaction and surveillance on the ground;
b. Collection, processing and accounting of data on their troops, the enemy and physical
and geographical conditions;
The military decision-making process
according to NATO standards (MDMP)
(Б А З А З Н А Н Ь)
Software-mathematical and information support of DSS
Stages (steps) of the military decision-making process
Stage (step) 1: Stage (step) 2: Stage (step) 3: Stage (step) 4: Stage (step) 5: Stage (step) 6: Stage (step) 7:
Development Analysis of
Getting a Analysis of of options for options for Comparison of Approval of a Issuance of an
combat combat combat action (COAs) options for course of action order or plan
operations and conducting (COA) (OPORD or
mission mission (COAs) a war game action
(COAs) OPLAN)
DSS software modules
INFORMATION EXCHANGE PROCESSING AND STORAGE OF INFORMATION AND
(Reception-transmission, INFORMATION SETTLEMENT
processing and storage of (IST, which are solved in the
commands, signals, orders, combat (Maintaining databases, processing and mechanized (tank) brigade (battalion)
documents) storing data of the current situation) of the LF of the AF of Ukraine)
Transmission of text messages, Processing and display of IST on the organization of
digital photos, files; video intelligence data; formation of a management, interaction and
conferencing, etc. unified operational and tactical reconnaissance of the area; IST
situation, etc. for situation assessment; support
for the development of the plan,
etc.
NAVIGATION SUPPORT CARTOGRAPHIC SUPPORT
(Continuous determination of
values of navigation parameters of (Solving geoformation problems)
ground mobile objects)
Determining the original Maintaining digital information
planned coordinates of the about the area; maintaining
machine, the current directional thematic information, etc.
angle of the machine and the
pitch angle, etc.
Sub-stages Tasks of governing Actions of governing
bodies bodies, result
Figure 1: Structure of SMaIS of ontological DSS of commanders of formations and units of the LF of
the Armed Forces of Ukraine
c. Assessment of the situation;
d. Marching opportunities;
e. Manoeuvrability;
f. Combat, shock, fire capabilities;
g. Operational support;
h. Technical support and combat service support [55];
Electronic forms of combat documents, which are worked out at the appropriate stages (sub-
stages);
Reference data used in the relevant stages of work, tips on how to perform specific tasks of
commanders (based on the requirements and recommendations of the relevant sections of NATO
standards);
Tactical examples;
References to guiding documents or their sections (chapters, paragraphs), which regulate the
implementation of specific tasks, etc.
Thus, the ontology is built to describe the algorithm of work of commanders in decision-making for
combat and to explain the abbreviation of the MDMP decision-making process according to NATO
standards based on knowledge formalized in the legal and regulatory framework for information
exchange, database structure. This ontology is used to implement models, methods, and operation of
individual DSS modules. In turn, such automation of each stage (step) of MDMP gives the chance to
reduce the time for decision-making as a whole. An example of automated design of ontologies (tasks
and SA), which was built during the work, is shown in Fig. 2 (fragment of SMaIS).
Figure 2: Hierarchy of the decision-making process by the commander (fragment)
The menu on the left displays the ontological model of the process work of commanders in decision-
making for combat (hierarchy of the commander's decision-making process). The figure also shows the
use of the built ontology to explain and describe the MDMP decision-making process according to the
standards of NATO member countries (menu on the right). The given ontology of planning the work of
commanders in decision-making for combat operations integrates the activities of the commander, staff,
subordinate, attached and interacting staffs in order:
Understand the situation and combat mission,
Develop and compare combat options (COAs - Courses of Action),
COA selection and development of a plan (OPORD - Operation Order);
An order to perform a combat mission, other documents.
The structure of DSS ontology determines the methods and algorithms that are necessary for
commanders of formations and units of the LF of the Armed Forces of Ukraine in the decision-making
process to solve the formal system [56-68].
The developed ontology of the process of commanders' decision-making in combat operations can
be considered as a component of the knowledge base of complex DSS for the LF of the AF of Ukraine.
It is a template for building a dynamic element in the knowledge base of such DSS, which changes from
one specific task in the military to another.
5. Conclusions
1. The main features of building a decision support system for commanders of formations and units
of the Land Forces of the Armed Forces of Ukraine, the central component of which is the
knowledge base, are considered. The core of such a knowledge base is the ontology of the
subject area.
2. The article is described the possible use of ontologies for a structured presentation of decision-
making and relevant components from the areas that represent such a process.
3. It is established that the SA of ontology is built to describe and explain the decision-making
process of MDMP according to the standards of NATO member countries. It is based on
knowledge formalised in guiding documents for information exchange, database structure, and
software implementation of models, methods and algorithms of individual DSS modules.
4. For model and form, an ontological decision support system by commanders of formations and
units of the Land Forces of the Ukrainian Armed Forces, a prototype of software, mathematics
and information support is developed. They can be used as a prototype of the future subsystem
of ACS of the LF of the Armed Forces of Ukraine.
5. The work algorithm process for the LF officials in the Ukrainian Armed Forces from the
battalion and above according to the US Armed Forces (MDMP) standards is proposed.
Automation of each stage (step) of MDMP gives the chance to reduce the time for decision-
making. This material can be used during the introduction into the educational process of
training officers and cadets of higher military educational institutions in the centre of simulation
and later for use in decision-making for combat operations in training canters and troops.
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