The model of market of one commodity , in which there are in each moment of time the same quantity and the same quantity of money was formulated and researched in this text. We also study this system as a game of automata.

This model is a replication of that described by Peterson (2002) and illustrates the ‘spread’ feedback loop type described in Millington (2013).

This model aims to mimic human movement on a realistic topographical surface. The agent does not have a perfect knowledge of the whole surface, but rather evaluates the best path locally, at each step, thus mimicking imperfect human behavior.

The model analyzes the economic and ecological effects of a provision of livestock drought insurance for dryland pastoralists. More precisely, it yields qualitative insights into how long-term herd and pasture dynamics change through insurance.

This is an agent-based model, simulating wolf (Canis Lupus) reappearance in the Netherlands. The model’s purpose is to allow researchers to investigate the reappearance of wolves in the Netherlands and the possible effect of human interference. Wolf behaviour is modelled according to the literature. The suitability of the Dutch landscape for wolf settlement has been determined by Lelieveld (2012) [1] and is transformed into a colour-coded map of the Netherlands. The colour-coding is the main determinant of wolf settlement. Human involvement is modelled through the public opinion, which varies according to the size, composition and behaviour of the wolf population.

[1] Lelieveld, G.: Room for wolf comeback in the Netherlands, (2012).

This model aims to simlulate the dynamic of risk over time and space.

Agers and non-agers agent compete over a spatial landscape. When two agents occupy the same grid, who will survive is decided by a random draw where chances of survival are proportional to fitness. Agents have offspring each time step who are born at a distance b from the parent agent and the offpring inherits their genetic fitness plus a random term. Genetic fitness decreases with time, representing environmental change but effective non-inheritable fitness can increase as animals learn and get bigger.

The core algorithm is an agent-based model, which simulates travel patterns on a network based on microscopic decision-making by each traveler.

Is the mass shooter a maniac or a relatively normal person in a state of great stress? According to the FBI report (Silver, J., Simons, A., & Craun, S. (2018). A Study of the Pre-Attack Behaviors of Active Shooters in the United States Between 2000 – 2013. Federal Bureau of Investigation, U.S. Department of Justice,Washington, D.C. 20535.), only 25% of the active shooters were known to have been diagnosed by a mental health professional with a mental illness of any kind prior to the offense.
The main objects of the model are the humans and the guns. The main factors influencing behavior are the population size, the number of people with mental disabilities (“psycho” in the model terminology) per 100,000 population, the total number of weapons (“guns”) in the population, the availability of guns for humans, the intensity of stressors affecting humans and the threshold level of stress, upon reaching which a person commits an act of mass shooting.
The key difference (in the model) between a normal person and a psycho is that a psycho accumulates stressors and, upon reaching a threshold level, commits an act of mass shooting. A normal person is exposed to stressors, but reaching the threshold level for killing occurs only when the simultaneous effect of stressors on him exceeds this level.
The population dynamics are determined by the following factors: average (normally distributed) life expectancy (“life_span” attribute of humans) and population growth with the percentage of newborns set by the value of the TickReprRatio% slider of the current population volume from 16 to 45 years old.Thus, one step of model time corresponds to a year.

FIBE represents a simple fishery model. Fish that reproduce and fisher with different fishing styles that fish as their main source of income. The aim of the model is to reflect the different fishing behaviours as described and observed in the (Swedish) Baltic Sea fishery and explore the consequences of different approximations of human/fisher behaviour in under different environmental and managerial scenarios.

The overarching aim is to advance the incorporation and understanding of human behaviour (diversity) in fisheries research and management. In particular focusing on insights from social (fishery) science of fisher behaviour.