Program packages method for solving closed-loop guidance problem with incomplete information for linear systems

The method of program packages [1] is a tool for identyfying the solvability conditions of guaranteed positional control problems when information on observed states is incomplete. In this talk a version of the method applicable to the problem of guaranteed positional guidance of a linear control system to a convex target set at a specified ti me is presented. The observed signal on the system’s states is assumed to be linear and the set of its admissible initial states is assumed to be finite. The method is based on clusterisation of the set of initial states according to the corresponding homogeneous signals and the moments of their separation from each other. A program package is a set of programs which are parametrized by the initial states and satisfying the ”non-anticipatory” condition. It is proved that the problem of guaranteed positional guidance is equivalent to the problem on the program package guidance which itself is equivalent to the program guidance of an extended linear control system to an extended convex target set [2]. For the latter problem a solvability criterion which reduces the task to the solution of a finite- dimensional optimization problem is produced using the separation theorem for convex sets. A procedure of construction the guiding program package and the corresponding guiding positional strategy which solves the given problem is described

Advancing the program packages method for positional control problems with incomplete information

Our presentation provides an overview of the program package method, a novel contribution to guaranteed control theory introduced by academicians Yu. S. Osipov and A. V. Kryazhimskiy in the late 2000s. The concept of program packages was developed to address problems of guaranteed guidance of dynamical systems amid incomplete information. The original problem setting was dedicated to guaranteed guidance of a controlled system onto a given target set at a predefined fixed time with incomplete information about its current phase state

Bouncing Forward Sustainably: Pathways to a post-COVID World. Strengthening Science Systems. Systems map.

Systems map depicting interlinkages among major issues relevant for the agility, reliability and science-policy-society interface as three dimensions of potential improvement of the science system to enhance its capability to respond to crises triggered by extreme events like COVID-19

Causal Loop Diagramming of Socioeconomic Impacts of COVID-19: State-of-the-Art, Gaps and Good Practices

The complexity, multidimensionality, and persistence of the COVID-19 pandemic have prompted both researchers and policymakers to turn to transdisciplinary methods in dealing with the wickedness of the crisis. While there are increasing calls to use systems thinking to address the intricacy of COVID-19, examples of practical applications of systems thinking are still scarce. We revealed and reviewed eight studies which developed causal loop diagrams (CLDs) to assess the impact of the COVID-19 pandemic on a broader socioeconomic system. We find that major drivers across all studies are the magnitude of the infection spread and government interventions to curb the pandemic, while the most impacted variables are public perception of the pandemic and the risk of infection. The reviewed COVID-19 CLDs consistently exhibit certain complexity patterns, for example, they contain a higher number of two- and three-element feedback loops than comparable random networks. However, they fall short in representing linear complexity such as multiple causes and effects, as well as cascading impacts. We also discuss good practices for creating and presenting CLDs using the reviewed diagrams as illustration. We suggest that increasing transparency and rigor of the CLD development processes can help to overcome the lack of systems thinking applications to address the challenges of the COVID-19 crisis

Development of various forms of security in the Arctic under different future socio-economic scenarios

Directions of the future development of the Arctic have been heavily debated in research and policy communities. The latest climate projections supported by an already observed significant sea ice retreat are leading various stakeholders to view the Arctic waters as a prospective commercial transportation route. Moreover, the increasing global demand for fossil resources and their abundance in the polar region are driving the development of new extraction projects. On the other hand, there are increasing calls to protect and preserve the delicate environment of the Arctic. The complexity of this environment is further aggravated by often competing interests of various actors: both Arctic and non-Arctic states, businesses, the local population, and indigenous peoples. Therefore, the Arctic is influenced by a plethora of global and regional factors. In the future, each of these factors may develop in several distinctly different directions. The multiplicity of combinations of such plausible developments of factors makes the strategic planning of activities in the Arctic prone to deep uncertainty. It makes it challenging for the governing actors to ensure various forms of security in the Arctic, such as economic security, energy security, environmental security, political security, health security, etc. In this paper, we present five extreme explorative scenarios covering the uncertainty space of the Euro-Asian Arctic development until 2050: (i) “Global Resource Base”, (ii) “Global Route”, (iii) “Abandoned Land”, (iv) “Sanctuary”, and (v) “Transpolar Shortcut”. Each scenario represents a unique combination of global and regional factor developments. The developed scenarios are loosely coupled with well-established global scenarios and are supported by an extensive literature review and expert inputs. In each scenario, the anticipated development of various forms of security in the Arctic is evaluated. The presented scenarios can be used by policymakers to better understand the future opportunities and threats they may face and to develop and evaluate corresponding policy measures. They can serve as an aid to develop a robust policy portfolio aiming at achieving acceptable levels of various forms of security under a range of global and regional developments

Applicability of the Future State Maximization Paradigm to Agent-Based Modeling: A Case Study on the Emergence of Socially Sub-Optimal Mobility Behavior

Novel developments in artificial intelligence excel in regard to the abilities of rule-based agent-based models (ABMs), but are still limited in their representation of bounded rationality. The future state maximization (FSX) paradigm presents a promising methodology for describing the intelligent behavior of agents. FSX agents explore their future state space using “walkers” as virtual entities probing for a maximization of possible states. Recent studies have demonstrated the applicability of FSX to modeling the cooperative behavior of individuals. Applied to ABMs, the FSX principle should also represent non-cooperative behavior: for example, in microscopic traffic modeling, there is a need to model agents that do not fully adhere to the traffic rules. To examine non-cooperative behavior arising from FSX, we developed a road section model populated by agent-cars endowed with an augmented FSX decision making algorithm. Simulation experiments were conducted in four scenarios modeling various traffic settings. A sensitivity analysis showed that cooperation among the agents was the result of a balance between exploration and exploitation. We showed that our model reproduced several patterns observed in rule-based traffic models. We also demonstrated that agents acting according to FSX can stop cooperating. We concluded that FSX can be useful for studying irrational behavior in certain traffic settings, and that it is suitable for ABMs in general