Georg Jäger

University of Graz | KFU Graz · Department of System Sciences, Innovation and Sustainability Research (ISIS)

Many systems in various scientific fields like medicine, ecology, economics or climate science exhibit so-called critical transitions, through which a system abruptly changes from one state to a different state. Typical examples are epileptic seizures, changes in the climate system or catastrophic shifts in ecosystems. In order to predict imminent...

Critical transitions can be conceptualized as abrupt shifts in the state of a system typically induced by changes in the system’s critical parameter. They have been observed in a variety of systems across many scientific disciplines including physics, ecology, and social science. Because critical transitions are important to such a diverse set of s...

Agent-based modelling is a powerful tool when simulating human systems, yet when human behaviour cannot be described by simple rules or maximizing one’s own profit, we quickly reach the limits of this methodology. Machine learning has the potential to bridge this gap by providing a link between what people observe and how they act in order to reach...

Traditional agent-based modelling is mostly rule-based. For many systems, this approach is extremely successful, since the rules are well understood. However, for a large class of systems it is difficult to find rules that adequately describe the behaviour of the agents. A simple example would be two agents playing chess: Here, it is impossible to...

Plain language summary Modelling electricity demand from charging electric cars Moving from cars with gasoline engines to electric cars is an important part of the shift toward a transportation system that doesn’t harm the environment. However, this change results in a significant increase in the need for renewable electric power. In this study, we...

Great effort is put into making our mobility system more sustainable in order to mitigate climate change. One corner stone of this endeavour is the transition from internal combustion engines to electric engines for private cars. This transition, however, introduces new challenges, especially regarding the demand for electrical energy from renewabl...

Contagions refer to the spread or transmission of diseases, behaviors, beliefs, or emotions. While some contagions easily propagate throughout entire populations, others seem to be more constrained and propagate only within specific parts of the population. This arises not just because of different transmission rates but because of qualitative diff...

The COVID-19 pandemic has underscored the importance of understanding, forecasting, and avoiding infectious processes, as well as the necessity for understanding the diffusion and acceptance of preventative measures. Simple contagions, like virus transmission, can spread with a single encounter, while complex contagions, such as preventive social m...

In many European countries with plentiful forest resources, novel forest‐based businesses play a key role in the transition from our current fossil‐based economy towards a circular bioeconomy. For example, kraft lignin, a by‐product from the pulping industry, is produced in large amounts globally. To date, however, it is still only offered on the m...

Critical transitions describe a phenomenon where a system abruptly shifts from one stable state to an alternative, often detrimental, stable state. Understanding and possibly preventing the occurrence of a critical transition is thus highly relevant to many ecological, sociological, and physical systems. In this context, it has been shown that the...

[This corrects the article DOI: 10.1371/journal.pone.0277347.].

Traditional models of social influence typically use assimilative or repulsive influence to study how consensus or polarization emerge. Given simple network structures, such as fully connected graphs, traditional models often fail to account for the multi-modal opinion distributions found in empirical data. In this study, we focus on more realistic...

A contagion can be conceptualized as the process of spreading an entity such as a virus, emotion, or information through a group or network. Depending on the kind of contagion, not all connections may contribute equally to the spreading success of a contagion. In this regard, it can be distinguished between a simple and a complex contagion where th...

Zusammenfassung Der vorliegende Beitrag befasst sich mit der Verteilung von (Berufs) Kompetenzen in der Steiermark. Für die Analyse der sozialen Ungleichheit in einer Region bietet dieser Ansatz eine Möglichkeit potenzielle Risiken und Chancen der Region aufzuzeigen, da anhand der Berufskompetenz-Landschaft Rückschlüsse über mögliche Ungleichheiten...

Methods to forecast critical transitions, i.e. abrupt changes in systems’ equilibrium states have relevance in scientific fields such as ecology, seismology, finance and medicine among others. So far, the bulk of investigations on forecasting methods builds on equation-based modeling methods, which consider system states as aggregates and thus do n...

Studies on the possibility of predicting critical transitions with statistical methods known as early warning signals (EWS) are often conducted on data generated with equation-based models (EBMs). These models base on difference or differential equations, which aggregate a system’s components in a mathematical term and therefore do not allow for a...

Recent research suggests that new technologies are important drivers of empirically observed labour market polarisation. Many analyses in the field of economics are conducted to evaluate the changing share of employment in low-skill, medium-skill and high-skill occupations over time. This occupation-based approach, however, may neglect the relevanc...

Agent-based modelling is a powerful tool when simulating human systems, yet when human behaviour cannot be described by simple rules or maximising one's own profit, we quickly reach the limits of this methodology. Machine learning has the potential to bridge this gap by providing a link between what people observe and how they act in order to reach...

Traffic and transportation are main contributors to the global CO2 emissions and resulting climate change. Especially in urban areas, traffic flow is not optimal and thus offers possibilities to reduce emissions. The concept of a Green Wave, i.e., the coordinated switching of traffic lights in order to favor a single direction and reduce congestion...

We investigate the possibility to apply a method of calculus analytics developed for predicting critical transitions in complex systems to social systems modelled with agent-based methods (ABMs). We introduce this method on the example of an equation-based modelled system and subsequently test it—to our knowledge for the first time—on ABMs. Our exp...

InPlakolb, SimonthisJäger, GeorgstudyHofer, ChristianweFüllsack, Manfred investigate the different effects of urban and rural mobility behaviour on congestion and emissions. For this we use a mesoscopic hybrid agent-based network traffic model to simulate traffic in a city on a 1:1 scale. The main advantage of the used model is that it does not nee...

Kapeller, Marie L.Jr, GeorgFllsack, ManfredHow people react towards threatening information such as climate change is a non-trivial matter. While people with a high environmental self-identity tend to react approach-motivated by engaging in pro-environmental behaviour, people of low environmental self-identity may exhibit proximal defence behaviour...

We devise an algorithm that can automatically identify entry and exit nodes of an arbitrary traffic network. It is applicable even if the network is of irregular shape, which is the case for many cities. Additionally, the method can calculate the nodes' attractiveness to commuters. This technique is then used to improve a traffic model, so that it...

We devise an algorithm that can automatically identify entry and exit nodes of an arbitrary traffic network. It is applicable even if the network is of irregular shape, which is the case for many cities. Additionally, the method can calculate the nodes' attractiveness to commuters. This technique is then used to improve a traffic model, so that it...

Context: Many AI and machine-learning techniques are primarily focused on past-to-future extrapolations of statistical regularities in large amounts of data. We introduce a method that builds on an in-action sampling of probes from possible futures with preference for those that prove promising for maximizing the perceivable space of possibilities....

Particulate matter pollution, especially in an urban environment, is a health risk that affects many people, and the current trend shows that these problems will increase in the near future. To combat this form of air pollution, many different strategies and policies are investigated: from reducing the emission of particulate matter to finding ways...

We present results of attempts to expand and enhance the predictive power of Early Warning Signals (EWS) for Critical Transitions (Scheffer et al. 2009) through the deployment of a Long-Short-Term-Memory (LSTM) Neural Network on agent-based simulations of a Repeated Public Good Game, which due to positive feedbacks on experience and social entrainm...

In order to meet the challenges of sustainable development, it is of utmost importance to involve all relevant decision makers in this process. These decision makers are diverse, including governments, corporations and private citizens. Since the latter group is the largest and the majority of decisions relevant to the future of the environment is...

Our current labour market is affected by massive changes like digitalization, automation and globalization, which gives rise to completely new forms of generating income. One such innovative idea is crowdworking, where many people (a so-called crowd) work on individual tasks for a firm in a way similar to a self-employed freelancer. This form of oc...

The footprint of tourism through travel is contributing significantly to the accumulation of human-made CO2. Due to different options in transportation, resulting emissions depend strongly on the choices of individuals on how to travel. In Austria, land travel is the main mode of transportation, though air travel has shown a significant increase du...

Abstract In the standard situation of networked populations, link neighbours represent one of the main influences leading to social diffusion of behaviour. When distinct attributes coexist, not only the network structure, but also the distribution of these traits shape the typical neighbourhood of each individual. While assortativity refers to the...

Agent-based modelling is a successful technique in many different fields of science. As a bottom-up method, it is able to simulate complex behaviour based on simple rules and show results at both micro and macro scales. However, developing agent-based models is not always straightforward. The most difficult step is defining the rules for the agent...

How people react to threatening information such as climate change is a complicated matter. While people with a high environmental self-identity tend to react approach-motivated by engaging in pro-environmental behaviour, people of low environmental self-identity may exhibit proximal defence behaviour, by avoiding and distracting themselves from po...

How people react to threatening information such as climate change is a complicated matter. While people with a high environmental self-identity tend to react approach-motivated by engaging in pro-environmental behaviour, people of low environmental self-identity may exhibit proximal defence behaviour, by avoiding and distracting themselves from po...

The increasing use of electric vehicles, combined with the trend of higher charging currents, puts a significant strain on the electrical grid. Many solutions to this problem are being discussed, some relying on some form of smart grid, others proposing stricter regulations concerning charging electric vehicles. In this study, a different approach,...

Motorized transport is one of the main contributors to anthropogenic CO 2 emissions, which cause global warming. Other emissions, like nitrogen oxides or carbon monoxide, are detrimental to human health. A prominent way to understand and thus be able to minimize emissions is by using traffic simulations to evaluate different scenarios. In that way,...

In this study elementary cellular automata are used to model the process of generating new knowledge. Each research goal is formulated as a target state of an elementary cellular automaton, while the scientific method used to reach this goal is represented as a rule. This system has many similarities to the actual process of knowledge generation, m...

Scanning a system's dynamics for critical transitions, i.e. sudden shifts from one system state to another, with the methodology of Early Warning Signals has been shown to yield promising results in many scientific fields. So far however, such investigations focus on aggregated system dynamics modeled with equation-based methods. In this paper the...

Background: Understanding traffic is an important challenge in different scientific fields. While there are many approaches to constructing traffic models, most of them rely on origin–destination data and have difficulties when phenomena should be investigated that have an effect on the origin–destination matrix. Methods: A macroscopic traffic mo...

CO2 emissions caused by private motorized traffic for the city of Graz, a typical European inland city with about 320 000 citizens, are investigated. The main methodology is a newly developed agent-based model that incorporates empirical data about the mobility behavior of the citizens in order to calculate the traveled routes, the resulting traffi...

We present a novel network approach, supported by an agent-based simulation using empirical survey results, in order to generate origin-destination data and information about the road usage of a large, urban traffic system. Additionally, we investigate congestion and its effects on road usage due to traffic jam avoidance strategies. The investigate...

Critical transitions of complex systems can often be predicted by so-called early-warning signals (EWS). In some cases, however, such signals cannot be detected although a critical transition is imminent. Observing a relation of EWS-detectability and the network topology in which the system is implemented, we simulate and investigate scale-free net...

We theoretically investigate the creation of squeezed states of a Bose-Einstein Condensate (BEC) trapped in a magnetic double well potential. The number or phase squeezed states are created by modulating the tunnel coupling between the two wells periodically with twice the Josephson frequency, i.e., through parametric amplification. Simulations are...

We study optimal quantum control of the dynamics of trapped Bose-Einstein condensates: The targets are to split a condensate, residing initially in a single well, into a double well, without inducing excitation; and to excite a condensate from the ground to the first excited state of a single well. The condensate is described in the mean-field appr...

We theoretically investigate protocols based on optimal control theory (OCT) for manipulating Bose-Einstein condensates in magnetic microtraps, using the framework of the Gross-Pitaevskii equation. In our approach we explicitly account for filter functions that distort the computed optimal control, a situation inherent to many experimental OCT impl...

We present theoretical and experimental results on high-fidelity transfer of a trapped Bose-Einstein condensate into its first vibrationally excited eigenstate. The excitation is driven by mechanical motion of the trap, along a trajectory obtained from optimal control theory. Excellent agreement between theory and experiment is found over a large r...