Palliative systems with simulation activity: resilience factors and management scenarios

Gribkov Andrei Armovich ORCID: 0000-0002-9734-105X Doctor of Technical Science Leading researcher; Scientific and production complex 'Technological Center' 124498, Russia, Moscow, Shokin square, 1, building 7 andarmo@yandex.ru Other publications by this author

Introduction

The subject of research within the framework of various theories of systems, including general systems theory, cybernetics (including control theory based on it), system analysis, system engineering, synergetics, etc., are existing and created systems, the representation of which corresponds to their real properties. A separate subject of consideration is ensuring the stability of systems under known external influences and deviations of system parameters from the initial stable state.

In practice, the problem of ensuring survivability ^[1] is also relevant, related to the preservation of damaged and incomplete (with missing structural elements) systems over a limited period of time (transition period), the degree and nature of which deviation from the stable state is unknown. During the specified transition period, the system is restored under the influence of internal self-organizing factors or external control, transformed, and its hibernation occurs (transition to a "dormant" state) or termination (stopping, destruction). During the transition period, the system is unable to implement the full range of its inherent functions; in the extreme case, the system can retain only one function – preservation during the transition to a stable state that coincides with the previous stable state, or a new one corresponding to the changes that have occurred in the system.

The problem of ensuring survivability is relevant for systems of various natures: economic, technical, social, psycho-emotional, etc. In relation to economic systems, the search for solutions to ensure survivability in the face of abrupt or catastrophic changes leading to partial destruction of the economic system is carried out in the context of regional specifics ^[2], country ^[3], etc. A separate area of research in the field of survivability of economic systems and individual industries was initiated by the COVID-19 epidemic ^[4]. A wide range of studies is also observed in the field of survivability of information and technical systems ^[5,6], social systems ^[7], including the viability of the family under stress of various origins based on protective factors and family resources, assuming the ability and willingness of the family to cope, change, adapt and develop ^[8].

The theoretical significance and practical value of the research conducted so far is beyond doubt. However, the accumulated knowledge in the field of survivability remains fragmented and fragmented, with significant specifics of the subject areas in which they are formed. In addition, palliative care systems remain outside the scope of research, the analysis of which is the main task of this article. Palliative care systems should not be confused with them, which are not palliative care themselves (they are quite functional and complete). Palliative care systems in this case are patients who cannot be cured, but for whom supportive therapy is possible.

The palliative system (from "palliative" – a non-exhaustive, temporary solution, a half-measure that covers, like a "cloak" (Latin pallium), the problem itself) is a special case of a transitional state of the system. The palliative care system simulates the "normal" functioning of a damaged system by replacing damage and incompleteness with "plugs" or elements with imitation activity. We will call plugs elements that do not have functionality, but nominally occupy the positions of damaged or missing functional elements. Elements with simulated activity are elements that do not have the functionality required for the system, but are able to interact with intact functional elements, simulating plausible reactions. In the simplest case, this imitation can be a repetition of reactions before damage or a continuation of emerging trends (inertia), in a more complex case, it can be an interpolation or extrapolation determined on the basis of previous reactions and changed effects from intact functional elements.

In the context of this goal of preserving damaged and incomplete systems, several key questions arise, the answers to which determine the management strategy and tactics that ensure long-term sustainability. These key issues addressed in this study include: determining mechanisms for ensuring sustainability in palliative systems, options for implementing plugs and elements with simulated activity, and possible scenarios for managing a palliative (damaged or incomplete) system.

The object of research is damaged and incomplete systems of any nature: technical, socio-economic, biological, managerial, etc. Such a broad formulation of the question is due to the specifics of the analysis inherent in the general theory of systems and the system approach as a whole, which is accepted as the main methodological basis of this study. The concepts of stability, management, feedback mechanisms, adaptability and evolution of systems, which are the basis of the analysis, are formed in accordance with the existing concepts of general theories of systems, including the empirical-metaphysical general theory of systems developed by the author ^[9].

Sustainability and management

In many cases, ensuring the stability of complex systems cannot be implemented as a local reaction to external destabilizing influences. This is due to the fact that the reaction of a complex system, corresponding to maintaining stability, is determined by the entire system or its part, which is significantly larger than the one that directly undergoes external influence.

The control (regulation) of a system with low complexity is carried out through a feedback mechanism, that is, the intensity of the system's response is determined by the magnitude of the deviation of its state from the required (stable) one ^[10]. Usually, negative feedback is required to ensure stability, when feedback is used to reduce the difference between the required and actual condition of the object. In the case of complex multicomponent and multiconnected systems, the direct use of the feedback mechanism is not enough to ensure the stability of the system ^[11].

In this case, how does the system "know" how to react correctly to external influences? Due to the existence of a model ^[12] of the system in one form or another, which shows how it should work correctly. In the case of artificially created systems, this model can be in the form of a plan or structure of a financial organization, a drawing of a machine and a description of its operation, a diagram of synchronized traffic flows, a mathematical model of the movement of the working body of technological equipment, etc. In the case of natural biological systems, it is used as a record of the genetic sequence in the DNA helix, verifiable and permanently reproducible RNA, etc. ^[13].

Is there an accurate match between the model and the actual system it serves to maintain? Absolutely not. The correspondence is not complete: the real system is in a state of constant change, its parameters are variable (but in the case of stability they do not exceed the limits of permissible deviations). Moreover, the system can change: evolve, transform in the process of adaptation, or degrade. The model is not a reflection or an ideal representation of a real system, it is needed for control, i.e., to coordinate the parameters of the elements of this system to ensure its stability and proper functioning.

What does the system do in case of damage or incompleteness, when it gets significant differences from its model? There are only two options: the system redefines its model, or it functions according to a model that no longer fully corresponds to it.

The option of redefining the model in the case of a rather complex system is difficult to implement ^[14]: the components of the system form a complex composition formed by structural and functional subsystems, the balance and correlation of which is achieved only after prolonged development (in the case of artificial systems), or prolonged evolution (in the case of living systems).

The option of functioning according to a model that differs from the system, in the case of not too big differences, is possible. Management is suboptimal, some management operations are impossible or cannot be performed correctly, some management operations do not have a destination, etc. Nevertheless, the complex of control actions generally corresponds to the system, and, in the vast majority of cases, contributes to a change in the state of the system in the direction of greater stability.

Complex multiconnected systems ensure their stability not only at the system level, but also at the subsystem level, a significant part of which, even in a damaged or incomplete system, retains its integrity or is slightly damaged. Mechanisms for ensuring stability in complex multiconnected systems are redundant ^[15]. This allows the system as a whole to restore its stability due to its constituent subsystems.

A significant mechanism for ensuring the stability of damaged and incomplete systems is also the stabilizing effect of the suprasystem. Any system does not exist by itself, its properties, the limitations of their changes, the very limits of stability are related to the nature of its suprasystem. The stability of the suprasystem is realized, among other things, through the integration of its constituent systems, the mutual influence of which contributes to the stability of the suprasystem as a whole and its constituent systems individually.

Stubs and simulation activity

We have already defined plugs and elements with simulation activity. Let's look at them in more detail.

The existing ideas about the elements that play the role of "stubs" are mainly related to the field of programming. Stub functions are used in programming, which are small program procedures that replace longer programs that do not perform any meaningful action, return an empty result or input data in unchanged form, and stub objects that return some kind of pre-recorded data, the reliability of which is not important (for example, when testing database performance, data reliability is not the purpose of verification). In computer network architecture, stubs are used to test ports, interfaces, and device connections, which are small devices inserted into a network communication port. Such plugs create a loopback circuit, that is, they redirect outgoing signals to the same device, simulating a full communication cycle.

In social and economic systems, the role of stub elements can also be significant. By replacing (nominally, without functionality) the real elements of a stub social or economic system, they preserve the integrity and coherence of the entire system, for which in many cases (especially within a limited time) only the nominal presence of an element, rather than its functioning, is sufficient. The absence of police officers in the area will not provoke an increase in crime if the offenders are unaware of the absence of police, the shortage of certain essential goods will not provoke (at least for a certain period of time) panic among consumers if this shortage is unknown, etc.

The socio-economic mechanism is complex and includes many elements, the usefulness of which cannot be unequivocally assessed. Failure of such elements does not lead to any significant negative consequences. At the same time, such elements are integrated into existing systems, the functioning of other elements presupposes their presence (for example, at the legal level), therefore, such elements should nominally be present in the system. As an example (indisputable), we can cite individual control bodies (fire safety, sanitary control, etc.), the degree of corruption of which in many cases makes their functionality extremely low. However, they are provided for by law and their elimination is impossible without stopping the economic activity associated with them.

It should be noted that stating the inevitability of using plug elements in complex systems does not justify their preservation. Another issue is that the immediate elimination of stubs is not always justified from the point of view of maintaining the stability of systems and minimizing resource consumption. Plugs self–destruct, systems are rebuilt and adapted - restoring an active functional element in place of the plug is not the only possible solution to the problem of correcting system defects.

Elements with simulated activity can exhibit two main types of activity.

Firstly, elements with imitation activity can functionally replace the original (damaged or missing) elements. To do this, an element with simulated activity must have adaptability – the ability to change its response to influences from other elements or in response to external influences on the system, corresponding (to a greater or lesser extent) to how it would be in the case of an intact and complete system. If it is possible to form an element with simulated activity that fully reproduces the reaction of the replaced element, then the replaced element is probably redundant and can be excluded from the system as an active element. In particular, such an element can be emulated (in full or in part) by a simulation model of the systems.

Ensuring the adaptability of an element with simulation activity is realized by giving it additional functionality, different from the original one of the replaced element, which consists in modeling (by software, hardware, etc.) the behavior of the replaced element, or interpolating and extrapolating its reaction based on an array of recorded reaction data of the intact element for various input conditions.

Secondly, elements with simulated activity can produce a repetitive (corresponding to the reaction before damage) or random (variable near the reaction before damage) reaction to exposure. Such elements with simulated activity do not have useful functionality. The preservation of an incomplete system or a system with damaged elements, replaced by such elements with simulated activity, is based on redundancy of connections in the system, replacement of functions of damaged or missing elements due to functioning elements and other mechanisms of stability of complex multiconnected systems. In living systems and other systems with nonequilibrium stability, it is possible to gradually redefine connections (flows in functional subsystems), as a result of which elements with simulation activity are gradually excluded from the system structure, taking the place of damaged and missing elements.

Scenarios for managing a damaged/incomplete system

In the case where the object of consideration is an externally controlled system, there are four possible scenarios for its management in case of damage or incompleteness.

The implementation of the first of the possible scenarios occurs when a damaged/missing element is not necessary to ensure the functionality of the system, or may lose its significance during the natural development of the system.

An example of such a scenario is a change in the composition of the consumer basket, from which goods previously positioned as essential goods are excluded over time. In particular, vegetable fats and margarine, some types of bread and other flour products, etc. are gradually excluded from the food component of the basket. If there is a shortage of such goods on the market, it is usually not overcome by an increase in supply, but gradually disappears by itself, as demand naturally decreases.

Another example of the implementation of the first scenario is from the field of medicine. Some organs of the human body are not necessary for its viability, although they have some (limited) impact on the quality of life. Examples of such organs are: appendix (appendix) (it is known that it has an immune function and has a positive effect on the maintenance of microflora in the body, but is not necessary ^[16]), adrenal glands (removal of one adrenal gland does not actually affect the quality of life; on the other hand, the preservation of the adrenal gland in case of occurrence in it tumors greatly increase the complexity of the operation and the risk to the patient's life ^[17]).

The second possible scenario for managing a damaged system is based on its adaptation to a changed state. At the same time, the system may redefine connections, allowing it to dispense with a lost/damaged element. This often happens in live systems. For example, the nervous system of animals and humans can restore its functionality even with significant mechanical damage, accompanied by significant losses of brain tissue, electrical or chemical damage. This recovery occurs due to the formation of nerve impulse transmission channels bypassing the damaged areas of the nervous system ^[18].

Along with redefining the connections in the system (a special case of which is the exclusion of damaged elements from circulatory processes that determine functional subsystems), it is also possible to restore the elements in their original or modified form. The initiation of such restoration and the models according to which restoration takes place are formed by other (intact) elements of the existing functional subsystems. The given nature of the links and constraints may be sufficient information to restore the element to its previous or alternative form, including simplified ones.

The third possible scenario is realized based on the results of monitoring an incomplete/damaged system with a plug or an element with simulated activity. If the system demonstrates acceptable functionality, then the option of using the system in a form different from the original one becomes relevant. For this "truncated" system, it is necessary to form a new model corresponding to it, probably less complex than the original one. An example of this scenario is a car in which some auxiliary functions have become unavailable, such as security systems, cruise control, climate control, autopilot, etc. If repairs are unavailable, the car can be used without auxiliary functions. Another example is the loss of a kitchen by a family (as a result of a fire or an urgent need for additional living space) in a country with an established tradition and existing infrastructure for eating out (family restaurants, cafes, etc.), typical of some European countries, Vietnam, etc. In this case, the restoration of the kitchen's functionality may not happen, and the family's behavior model governing its household practices will be redefined. At the same time, over a certain period of time, depending on the presence of social restrictions (family traditions, the nature of friendly relations, etc.), the forge can be replaced by a plug – used as a room for eating, but not cooking.

The fourth possible scenario is the restoration of damaged or missing elements in the system in the case when all other scenarios do not allow you to get a system with acceptable functionality. Restoration does not occur immediately upon detection of damage or incompleteness, but based on the results of an analysis of all possible scenarios, an assessment of the possibilities for changing functionality, the resources required for restoration, and other factors. The time period from the detection of damage or incompleteness of the elements, these elements are replaced by plugs or elements with imitation activity. The degree to which the nature of the simulation activity approximates the nature of the original intact element is determined by the duration of its expected operation and the resources (material, energy, computing, financial, etc.) that can be spent on it.

Damaged/incomplete systems with nonequilibrium stability deserve special consideration. A comparative analysis of the behavior of different systems shows that systems with nonequilibrium stability ^[19,20], based on dynamic kinetic stability, have the greatest stability in case of damage ^[21]. This type of stability is inherent in living systems and other open dynamic systems that ensure their stability at the expense of the resources of the suprasystem ^{[9, pp. 106-114]} at a level corresponding to the activity of the system in question (as opposed to ensuring stability at one of the levels, whether it coincides with a lower one compared to the level of system activity implemented in any open system).

Why does maintaining the process (in systems with nonequilibrium stability) provide greater stability in case of damage than maintaining the structure or shape (in systems with conventional stability, requiring a balance of activities of the opposite orientation)? One of the reasons is greater adaptability due to the lower expenditure of system resources in the case of process adjustments (for example, circulatory) compared to shape or structure adjustments.

The higher adaptivity of systems with nonequilibrium stability is also associated with a higher rate of response of such systems to damage and external influences in general. The redefinition of the form and structure of the system does not occur continuously, but periodically. There is also a periodic redefinition of the effect of incompleteness or damage of system elements on other elements. As a result, in systems with conventional stability, the reaction to damage occurs with a significant delay, during which it significantly deviates from the initial state, which makes it difficult to correct.

In general, a reasonable assessment of the feasibility of a palliative system is based on two criteria that characterize the need to preserve a damaged/incomplete system and the need to simulate the preservation of integrity and activity.

In the detailed description, the first of these criteria reflects the existence of an objective need to maintain the system in a state of limited functionality or even, in the extreme case, with functionality limited by maintaining the stability of the system. When it comes to living systems (a human body or an animal body, a socio-economic system, an ecosystem, etc.), the need to maintain the system has good reasons, even if it is only about continuing to exist without preserving useful functionality.

A detailed description of the second criterion reveals the validity of the simulation activity or stubs for the damaged system, i.e. the nominal preservation of the system reproducing (more or less reliably) the reactions of the intact system. In general, it is advisable to use simulation activities and stubs for a limited period of time – a transition period after which the system transforms or ceases to exist. For some systems, for example, open dynamic systems, the possibilities of transition from a damaged or incomplete state to a new stable one turn out to be significantly large. The period of appropriate palliative care for such systems is significantly longer, and the options for transformation and adaptation are much broader.

The research presented in this article allows us to confirm the right to the existence of palliative care systems, including those with imitation activity. The expediency of such systems is not limited to maintaining the life of living beings, but can be objectively assessed for systems of various contents and applications.

Most complex multicomponent systems possess (to varying degrees) the properties of palliative care systems. Determining the specifics of their behavior and management scenarios are important tasks for which possible approaches to solving are outlined in this study. The development and expansion of the theoretical base in the field of palliative systems (as a variant of the long–term existence of damaged and incomplete systems) is a necessary direction for further research in the field of general systems theory and management theory, which has not yet received the necessary development.

Conclusions

Let's summarize the research conducted in the article:

1. Within the framework of system theories, the problem of preserving damaged and incomplete systems for a limited period of time is significant.

2. During the specified time period (transition period), the system may be in a palliative state, in which damaged or missing elements are replaced by plugs devoid of functionality, or by elements with simulated activity simulating the reactions of the original intact element and the complete system that includes it.

3. The system is maintained in a state of stability under external control by means of control actions regulated by the controlled system model. In case of damage or incompleteness of the system, the model ceases to fully comply with it.

4. Management of a damaged or incomplete system can be carried out on the basis of redefining its model, or using a model that does not fully correspond to the new state of the system. The second option is more effective in case of minor damage to the system.

5. Fixing damaged system elements or restoring system integrity is not the only solution to the problem of saving the system. Stubs and elements with simulated activity can also self-destruct, rebuild, adapt, or go into a passive state in which they lose their independent activity and are reproduced by software, hardware, or other means.

6. There are various alternative scenarios for managing a damaged or incomplete system. The choice of the optimal option depends on the continued importance of the system functions associated with damaged elements, the ability of the system to adapt, the usefulness of a system with "truncated" functionality, the degree of complexity and the amount of resources required to repair damage to the elements and restore system integrity.