Genetic algorithms try to solve a computational problem following some principles of organic evolution. This model has educational purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the candidate solutions to the problem are represented by agents, that in logo programming environment are usually known as “turtles”.

A first version of a model that describes how coalitions are formed during open, networked innovation

Cultural group selection model of agents playing public good games and who are able to punish and punish back.

Studies on word-of-mouth identify two behaviors leading to transmission of information between individuals: proactive transmission of information, and information seeking. Individuals who are aware might be curious of it and start seeking for information; they might find around them the expertise held by another individual. Field studies indicate individuals do not adopt an innovation if they don’t hold the corresponding expertise. This model describes this information seeking behavior, and enables the exploration of the dynamics which emerges out of it.

In this model, we simulate the navigation behavior of homing pigeons. Specifically we use genetic algorithms to optimize the navigation and flocking parameters of pigeon agents.

This model was created to investigate the potential impacts of large-scale recreational and transport-related physical activity promotion strategies on six United Nations Sustainable Development Goals (SDGs) related outcomes—road traffic deaths (SDG 3), transportation mode share (SDG 9), convenient access to public transport, levels of fine particulate matter, and access to public open spaces (SDG 11), and levels of carbon dioxide emissions (SDG 13)—in three cities designed as abstract representations of common city types in high-, middle-, and low-income countries.

This model demonstrates the spread of collapse through a network. The model is abstract but has many applications in various fields.

The model objective’s is to explore the management choice set to uncover which subsets of strategies are most effective at maximizing species coexistence on a fragmented landscape.

The model of Chinese and Western civilization patterns can help understand how civilizations formed, how they evolved by themselves, and the difference between the unity of China and the disunity of the Western. The previous research had examined historical phenomena about civilization patterns with subjective, static, local, and inductive methods. Therefore, we propose a general model of history dynamics for civilizations pattern, which contains both China and the West, to improve our understanding of civilization formation and the factors influencing the pattern of civilization. And at the same time, the model is used to find the boundary conditions of two different patterns.

Presented here is a socioeconomic agent-based model (ABM) to examine the Hollywood labor system as a network within a simulated movie labor market based on preferential attachment and compare the findings with 50 co-production ego networks during the 2015 movie year. Using the ABM, I test the role slight individual preference for racial and ethnic similarity within one’s own network at the microlevel and find that it is insufficient to explain the phenomena of racial and ethnic underrepresentation at the macrolevel. The ABM also includes the ability to test alternative explanations, such as overt opportunity loss as a possible explanation.