Socio-Ecological Systems (SES)

In this work, the spread of a contagious disease on a society where the individuals may take precautions is modeled. The primary assumption is that the infected individuals transmit the infection to the susceptible members of the community through direct contact interactions. In the meantime, the susceptibles gather information from the neighboring sites which may lead to taking precautions. The SIR model [1] is used for the diffusion of infection while the Bass equation [2] models the information diffusion.

In this contribution, we would like to make a few points how agent-based models, a fairly new protagonist in the area of model-based legal policy advice, can enrich the possibilities for the lawmaking profession to capture phenomena that seem to evade current mainstream lawmaking processes. Our additional aim is to spot issues that need to be addressed in order to make the approach acceptable to the mainstream law profession. The application area of our contribution is data protection law and the force of data protection regulation.

Possible future trajectories of the Earth system in the Anthropocene are determined by the increasing entanglement of processes operating in the physical, chemical and biological systems of the planet, as well as in human societies, their cultures and economies. Here, we introduce the copan:CORE open source software library
that provides a framework for developing, composing and running World-Earth models,

Despite their potential interplay, multiple routes of many disease transmissions are often investigated separately. As an unifying framework for understanding parasite spread through interdependent transmission paths, we present the 'ecomultiplex' model, where the multiple transmission paths among a diverse community of interacting hosts are represented as a spatially explicit multiplex network. We adopt this framework for designing and testing potential control strategies for T. cruzi spread in two empirical host communities.

Emergence of coordination among individual agents in a complex system, where there is no central authority controlling their actions, requires information transfer between them and the ability to respond appropriately. Often, the interactions between these agents recur and the information generated from these interactions collectively, takes the form of some global cues available to all agents of the complex system. Agents respond to such information by altering their behavior accordingly, which results in adaptive dynamics in the system.

We introduce a general framework for exploring the problem of selecting a committee of representatives with the aim of studying a networked voting rule based on a decentralized large-scale platform, which can assure a strong accountability of the elected [1]. The results of our simulations suggest that this algorithm-based approach is able to obtain a high representativeness for relatively small committees, performing even better than a classical voting rule based on a closed list of candidates.

The collapse of ecosystems, the extinction of species or the breakdown of
company networks, banking networks and political systems usually hinges
on topological properties of the underlying interaction network, such as
the existence of keystone nodes. Knowing just the macroscopic non-
structural information, such as species abundances, company revenues
etc, it seems impossible to make predictions about impending collapses of
these system. We show, however, that such macroscopic predictions are

Since the eighties of the last century, agent-based modeling has become both a complement and a substitute for more traditional economic-modeling methodologies. In macroeconomics, for example, agent-based models (ABMs) are nowadays considered as a valid and effective competitor of standard Dy- namic Stochastic General Equilibrium (DSGE) models [1]. Likewise, ABMs of financial markets are often considered better than traditional models based on the efficient-market hypothesis in explaining the statistical properties of buy- and-sell high-frequency dynamics [2].

Collective design and innovation processes have become a necessity for the development of successful solutions for most real-world problems. Such large-scale design processes typically involve individuals with diverse knowledge, expertise and behaviors, and the organizational structures under which the collective design takes place are often complex and dynamic.

The formation and stability of social hierarchies is a question of general relevance. Here, we propose a simple model for establishing social hierarchy via pair-wise interactions between individuals and investigate its stability. In each interaction or fight, the probability of "winning" depends solely on the relative societal status of the participants, and the winner has a gain of status whereas there is an equal loss to the loser. The interactions are characterized by two parameters.