This model is used to simulate the influence of spatially and temporally variable sedimentary processes on the distribution of dated archaeological features in a surface context.

This model is intended to explore the effectiveness of different courses of interventions on an abstract population of infections. Illustrative findings highlight the importance of the mechanisms for variability and mutation on the effectiveness of different interventions.

Comparing impact of alternative behavioral theories in a simple social-ecological system.

How can species evolve a cooperative network to keep the environment suitable for life?

This model simulates the Hawk-Dove game as first described by John Maynard Smith, and further elaborated by Richard Dawkins in “The Selfish Gene”. In the game, two strategies, Hawks and Doves, compete against each other, and themselves, for reproductive benefits. A third strategy can be introduced, Retaliators, which act like either Hawks or Doves, depending on the context.

An agent-based model designed as a tool to assess and plan free-ranging dog population management programs that implement Animal Birth Control (ABC). The time, effort, financial resources and conditions needed to successfully control dog populations and achieve rabies control can be determined by performing virtual experiments using DogPopDy.

Its a multi agent simulation environment, provided using JADE/Java. It gets the number of agents and tasks, then divides the physical environment to some segments, and then runs a greedy capability-based coalition formation and task allocation algorithm to assign tasks to groups of agents and complete the tasks.

The AMMA simulates how news waves emerge in the mass media. Drawing on the ideas of public arena models and issue-attention cycles, it represents fundamental principles of public communication in a virtual media system.

This model simulates the motion picture industry and tests how social influences affect market shares. It is empirically validated at the micro level by a cross-cultural survey.

The model is an agent-based artificial stock market where investors connect in a dynamic network. The network is dynamic in the sense that the investors, at specified intervals, decide whether to keep their current adviser (those investors they receive trading advise from). The investors also gain information from a private source and share public information about the risky asset. Investors have different tendencies to follow the different information sources, consider differing amounts of history, and have different thresholds for investing.