The model investigates conditions, scenarios and strategies for future planning of energy in Egypt, with an emphasis on alternative energy pathways and a sustainable electricity supply mix as part of an energy roadmap till the year 2100. It combines the multi-criteria decision analysis (MCDA) with agent-based modeling (ABM) and Geographic Information Systems (GIS) visualization to integrate the interactions of the decisions of multi-agents, the multi-criteria evaluation of sustainability, the time factor and the site factors to assess the transformation of energy landscapes.

This model has been developed together with the publication ‘Modelling Value Change - An Exploratory Approach’

Value change and moral change have increasingly become topics of interest in the philosophical literature. Several theoretical accounts have been proposed. Such accounts are usually based on certain theoretical and conceptual assumptions and their strengths and weaknesses are often hard to determine and compare, also because they are based on limited empirical evidence.

We propose that a step forward can be made with the help of agent-based modelling (ABM). ABM can be used to investigate whether a simulation model based on a specific account of value change can reproduce relevant phenomena. To illustrate this approach, we built a model based on the pragmatist account of value change proposed in van de Poel and Kudina (2022). We show that this model can reproduce four relevant phenomena, namely 1) the inevitability and stability of values, 2) how different societies may react differently to external shocks, 3) moral revolutions, and 4) lock-in.

The model is designed to simulate the behavior and decision-making processes of individuals (agents) in a social network. It aims to represent the changes in individual probability to take any action based on changes in attributes. The action is anything that can be reasonably influenced by the three influencing methods implemented in this model: peer pressure, social media, and state campaigns, and for which the user has a decision-making model. The model is implemented in the multi-agent programmable environment NetLogo 6.3.0.

A Picit Jeu is an agent-based model (ABM) developed as a supporting tool for a role-playing game of the same name. The game is intended for stakeholders involved in land management and fire prevention at a municipality level. It involves four different roles: farmers, forest technicians, municipal administrators and forest private owners. The model aims to show the long-term effects of their different choices about forest and pasture management on fire hazard, letting them test different management strategies in an economically constraining context. It also allows the players to explore different climatic and economic scenarios. A Picit Jeu ABM reproduces the ecological, social and economic characteristics and dynamics of an Alpine valley in north-west Italy. The model should reproduce a primary general pattern: the less players undertake landscape management actions, by thinning and cutting forests or grazing pastures, the higher the probability that a fire will burn a large area of land.

This model system aims to simulate the whole process of task allocation, task execution and evaluation in the team system through a feasible method. On the basis of Complex Adaptive Systems (CAS) theory and Agent-based Modelling (ABM) technologies and tools, this simulation system attempts to abstract real-world teams into MAS models. The author designs various task allocation strategies according to different perspectives, and the interaction among members is concerned during the task-performing process. Additionally, knowledge can be acquired by such an interaction process if members encounter tasks they cannot handle directly. An artificial computational team is constructed through ABM in this simulation system, to replace real teams and carry out computational experiments. In all, this model system has great potential for studying team dynamics, and model explorers are encouraged to expand on this to develop richer models for research.

The purpose of the model is to study the dynamical relationship between individual needs and group performance when focusing on self-organizing task allocation. For this, we develop a model that formalizes Deci & Ryan’s self-determination theory (SDT) theory into an ABM creating a framework to study the social dynamics that pertain to the mutual relations between the individual and group level of team performance. Specifically, it aims to answer how the three individual motivations of autonomy, competence, and belonging affect team performance.

The model explores food distribution patterns that emerge in a small-scale non-agricultural group when sharing individuals engage in intentional consumption leveling with a given probability.

This model is an application of Brantingham’s neutral model to a real landscape with real locations of potential sources. The sources are represented as their sizes during current conditions, and from marine geophysics surveys, and the agent starts at a random location in Mossel Bay Region (MBR) surrounding the Archaeological Pinnacle Point (PP) locality, Western Cape, South Africa. The agent moves at random on the landscape, picks up and discards raw materials based only upon space in toolkit and probability of discard. If the agent happens to encounter the PP locality while moving at random the agent may discard raw materials at it based on the discard probability.

The model reproduces the spread of environmental awareness among agents and the impact of awareness level of the agents on the consumption of a resource, like energy. An agent is a household with a set of available advanced smart metering functions.

The model examines the dynamics of herd growth in African pastoral systems. We used it to examine the role of scale (herd size) stochasticity (in mortality, fertility, and offtake) on herd growth.