An agent-based model is used to simulate legislators’ behavior under secret voting rules, as influenced by the power of the accused politician, the composition of the voting body, and the publicity of the accusations.

Captures interplay between fixed ethnic markers and culturally evolved tags in the evolution of cooperation and ethnocentrism. Agents evolve cultural tags, behavioural game strategies and in-group definitions. Ethnic markers are fixed.

This model builds on inquisitiveness as a key individual disposition to expand the bounds of their rationality. It represents a system where teams are formed around problems and inquisitive agents integrate competencies to find ‘emergent’ solutions.

This is a simulation model of an intelligent agent that has the objective to learn sustainable management of a renewable resource, such as a fish stock.

ARISE is a hybrid energy model incorporating macroeconomic data, micro socio-economic data, engineering data and environmental data. This version of ARISE can simulate scenarios of solar energy policy for Indonesia case.

Flibs’NLogo implements in NetLogo modelling environment, a genetic algorithm whose purpose is evolving a perfect predictor from a pool of digital creatures constituted by finite automata or flibs (finite living blobs) that are the agents of the model. The project is based on the structure described by Alexander K. Dewdney in “Exploring the field of genetic algorithms in a primordial computer sea full of flibs” from the vintage Scientific American column “Computer Recreations”
As Dewdney summarized: “Flibs […] attempt to predict changes in their environment. In the primordial computer soup, during each generation, the best predictor crosses chromosomes with a randomly selected flib. Increasingly accurate predictors evolve until a perfect one emerges. A flib […] has a finite number of states, and for each signal it receives (a 0 or a 1) it sends a signal and enters a new state. The signal sent by a flib during each cycle of operation is its prediction of the next signal to be received from the environment”

A simple model that aims to demonstrate the influence of agri-environmental payments on land-use patterns in a virtual landscape. The landscape consists of grassland (which can be managed extensively or intensively) and a river. Agri-environmental payments are provided for extensive management of grassland. Additionally, there are boni for (a) extensive grassland in proximity of the river; and (b) clusters (“agglomerations”) of extensive grassland. The farmers, who own randomly distributed grassland patches, make decisions either on the basis of simple income maximization or they maximize only up to an income threshold beyond which they seize making changes in management. The resulting landscape pattern is evaluated by means of three simple models for (a) agricultural yield, (b) habitat/biodiversity and (c) water quality. The latter two correspond to the two boni. The model has been developed within a small project called Aligning Agent-Based Modelling with Multi-Objective Land-Use Allocation (ALABAMA).

Resilience of humans in the Upper Paleolithic could provide insights in how to defend against today’s environmental threats. Approximately 13,000 years ago, the Laacher See volcano located in present-day western Germany erupted cataclysmically. Archaeological evidence suggests that this is eruption – potentially against the background of a prolonged cold spell – led to considerable culture change, especially at some distance from the eruption (Riede, 2017). Spatially differentiated and ecologically mediated effects on contemporary social networks as well as social transmission effects mediated by demographic changes in the eruption’s wake have been proposed as factors that together may have led to, in particular, the loss of complex technologies such as the bow-and-arrow (Riede, 2014; Riede, 2009).

This model looks at the impact of the interaction between climate change trajectory and an extreme event, such as the Laacher See eruption, on the generational development of hunter-gatherer bands. Historic data is used to model the distribution and population dynamics of hunter-gatherer bands during these circumstances.

An ABM of changes in individuals’ lifestyles which considers their
evolving behavioural choices. Individuals have a set of environmental behavioural traits that spread through a fixed Watts–Strogatz graph via social interactions with their neighbours. These exchanges are mediated by transmission biases informing from whom an individual learns and
how much attention is paid. The influence of individuals on each other is a function of their similarity in environmental identity, where we represent environmental identity computationally by aggregating past agent attitudes towards multiple environmentally related behaviours. To perform a behaviour, agents must both have
a sufficiently positive attitude toward a behaviour and overcome a corresponding threshold. This threshold
structure, where the desire to perform a behaviour does not equal its enactment, allows for a lack of coherence
between attitudes and actual emissions. This leads to a disconnect between what people believe and what
…

The publication and mathematical model upon which this ABM is based shows one mechanism that can lead to stable behavioral and cultural traits between groups.