A formalized implementation of Halstead and O’Shea’s Bad Year Economics. The agent population uses one of four resilience strategies in an attempt to cope with a dynamic environment of stresses and shocks.

This version 2.1.0 of the uFunk model is about setting a business strategy (the S in the name) for an organization. A team of managers (or executives) meet and discuss various options on the strategy for the firm. There are three aspects that they have to agree on to set the strategic positioning of the organization.
The discussion is on market, stakeholders, and resources. The team (it could be a business strategy task force) considers various aspects of these three elements. The resources they use to develop the discussion can come from a traditional approach to strategy or from non-traditional means (e.g., so-called serious play, creativity and imagination techniques).
The S-uFunk 2.1.0 Model wants to understand to which extent cognitive means triggered by traditional and non-traditional resources affect the making of the strategy process.

This model describes a mechanism by which software agents can identify norms in an artificial agent society. In particular, this model uses a sequence mining approach to identify norms in an agent soc

The model formalizes a situation where agents embedded in different types of networks (random, small world and scale free networks) interact with their neighbors and express an opinion that is the result of different mechanisms: a coherence mechanism, in which agents try to stick to their previously expressed opinions; an assessment mechanism, in which agents consider available external information on the topic; and a social influence mechanism, in which agents tend to approach their neighbor’s opinions.

This model is pertinent to our JASSS publication “Raising the Spectrum of Polarization: Generating Issue Alignment with a Weighted Balance Opinion Dynamics Model”. It shows how, based on the mechanisms of our Weighted Balance Theory (a development of Fritz Heider’s Cognitive Balance Theory), agents can self-organize in a multi-dimensional opinion space and form an emergent ideological spectrum. The degree of issue alignment and polarization realized by the model depends mainly on the agent-specific ‘equanimity parameter’ epsilon.

Due to the large extent of the Harz National Park, an accurate measurement of visitor numbers and their spatiotemporal distribution is not feasible. This model demonstrates the possibility to simulate the streams of visitors with ABM methodology.

Merger and acquisition (M&A) activity has many strategic and operational objectives. One operational objective is to develop common and efficient information systems that maybe the source of creating

The purpose of the study is to unpack and explore a potentially beneficial role of sharing metacognitive information within a group when making repeated decisions about common pool resource (CPR) use.

We explore the explanatory power of sharing metacognition by varying (a) the individual errors in judgement (myside-bias); (b) the ways of reaching a collective judgement (metacognition-dependent), (c) individual knowledge updating (metacognition- dependent) and d) the decision making context.

The model (AgentEx-Meta) represents an extension to an existing and validated model reflecting behavioural CPR laboratory experiments (Schill, Lindahl & Crépin, 2015; Lindahl, Crépin & Schill, 2016). AgentEx-Meta allows us to systematically vary the extent to which metacognitive information is available to agents, and to explore the boundary conditions of group benefits of metacognitive information.

The present model is an abstract ABM designed for theoretical exploration and hypotheses generation. Its main aim is to explore the relationship between disagreement over the diagnostic value of evidence and the formation of polarization in scientific communities.
The model represents a scientific community in which scientists aim to determine whether hypothesis H is true, and we assume that agents are in a world in which H is indeed true. To this end, scientists perform experiments, interpret data and exchange their views on how diagnostic of H the obtained evidence is. Based on how the scientists conduct the inquiry, the community may reach a correct consensus (i.e. a situation in which every scientist agrees that H is correct) or not.

This model test the efficiency of the market economy in comparison with a hunter/gatherer economy. It also compares the model outcomes between a market economy when using eternal agents with one using mortal agents.