This model simulates the mechanisms of evolution, or how allele frequencies change in a population over time.

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

This is a model of a game of Telephone (also known as Chinese Whishpers in the UK), with agents representing people that can be asked, to play. The first player selects a word from their internal vocabulary and “whispers” it to the next player, who may mishear it depending on the current noise level, who whispers that word to the next player, and so on.

When the game ends, the word chosen by the first player is compared to the word heard by the last player. If they match exactly, all players earn large prize. If the words do not match exactly, a small prize is awarded to all players for each part of the words that do match. Players change color to reflect their current prize-count. A histogram shows the distribution of colors over all the players.

The user can decide on factors like * how many players there are,
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This model aims to simulate Competition and Displacement of Online Interpersonal Communication Platforms process from a bottom-up angle. Individual interpersonal communication platform adoption and abandonment serve as the micro-foundation of the simulation model. The evolution mode of platform user online communication network determines how present platform users adjust their communication relationships as well as how new users join that network. This evolution mode together with innovations proposed by individual interpersonal communication platforms would also have impacts on the platform competition and displacement process and result by influencing individual platform adoption and abandonment behaviors. Three scenes were designed to simulate some common competition situations occurred in the past and current time, that two homogeneous interpersonal communication platforms competed with each other when this kind of platforms first came into the public eye, that a late entrant platform with a major innovation competed with the leading incumbent platform during the following days, as well as that both the leading incumbent and the late entrant continued to propose many small innovations to compete in recent days, respectively.
Initial parameters are as follows: n(Nmax in the paper), denotes the final node number of the online communication network node. mi (m in the paper), denotes the initial degree of those initial network nodes and new added nodes. pc(Pc in the paper), denotes the proportion of links to be removed and added in each epoch. pst(Pv in the paper), denotes the proportion of nodes with a viscosity to some platforms. comeintime(Ti in the paper), denotes the epoch when Platform 2 joins the market. pit(Pi in the paper), denotes the proportion of nodes adopting Platform 2 immediately at epoch comeintime(Ti). ct(Ct in the paper), denotes the Innovation Effective Period length. In Scene 2, There is only one major platform proposed by Platform 2, and ct describes that length. However, in Scene 3, Platform 2 and 1 will propose innovations alternately. And so, we set ct=10000 in simulation program, and every jtt epochs, we alter the innovation proposer from one platform to the other. Hence in this scene, jtt actually denotes the Innovation Effective Period length instead of ct.

B3GET Classic includes previous versions used in the classroom and for publication. Please check out the latest version of B3GET here, which has several user-friendly features such as directly importing and exporting genotype and population files.

The classic versions of B3GET include: version one was and version three is currently used in undergraduate labs at the University of Minnesota to demonstrate principles in primate behavioral ecology; version two first demonstrated proof of concept for creating virtual biological organisms using decision-vector technology; version four was presented at the 2017 annual meeting at the American Association of Physical Anthropologists; version five was presented in a 2019 publication from the Journal of Human Evolution (Crouse, Miller, and Wilson, 2019).

The ana-wag model, for Analyse Wat-A-Game (WAG), is a NetLogo version of the WAG role playing game. It enables to model a river catchment with the graphical modelling language WAG and to play it as a network-game (each player is a water user).

The computer model simulates the development of a social network (i.e. formation of friendships and cliques), the (dyadic) interactions between pupils and the development of similarities and differences in their behavioral profiles.

Brazil has initiated two territorial public policies for a rural sustainable development, the National Program for Sustainable Development of the Rural Territories (PRONAT) and Citizenship Territory Program (PTC). These public policies aims, as a condition for its effectiveness, the equilibrium of the power relations between actors which participate in the Collegiate for Territorial Development (CODETER) of each Rural Territory. Our research studies the hypotheses that, in the Rural Territories submitted to the PRONAT and PTC public policies, the power and reciprocity relations between actors engaged in the CODETER effectively have evolved in favor of the civil society representatives to the detriment of the public powers, notably the mayors.

The SocLab approach has been applied in two case studies and four models representing the Southern Rural Territory of Sergipe (TRSS) and the São Francisco Rural Territory (TRBSF) were designed for two referential periods, 2008-2012 and 2013-2017. These models were developed to evaluate the empowerment of the civil society in these rural territories due to thes two public policies, PRONAT and PTC.

This is a modification of the RobbyGA model by the Santa Fe Institute (see model Info tab for full information). The basic idea is that the GA has been changed to one where the agents have a set lifetime, anyone can reproduce with anyone, but where there is a user-set amount of ‘starvation’ that kills the agents that have a too low fitness.

An agent-based simulation of a game of basketball. The model implements most components of a standard game of basketball. Additionally, the model allows the user to test for the effect of two separate cognitive biases – the hot-hand effect and a belief in the team’s franchise player.