This code simulates the WiFi user tracking system described in: Thron et al., “Design and Simulation of Sensor Networks for Tracking Wifi Users in Outdoor Urban Environments”. Testbenches used to create the figures in the paper are included.

A simple model to assess the effect of connectivity on interacting species (i.e. predator-prey type)

Knowledge Space model of Opinion Dynamics.

Routes & Rumours is an agent-based model of (forced) human migration. We model the formation of migration routes under the assumption that migrants have limited geographical knowledge concerning the transit area and rely to a large degree on information obtained from other migrants.

This simulation model is to simulate the emergence of technological innovation processes from the hypercycles perspective.

This model takes concepts from a JASSS paper this is accepted for the October, 2023 edition and applies the concepts to empirical data from counties surrounding and including Cleveland Ohio. The agent-based model has a proportional number of agents in each of the counties to represent the correct proportions of adults in these counties. The adoption decision probability uses the equations from Bass (1969) as adapted by Rand & Rust (2011). It also includes the Outgroup aversion factor from Smaldino, who initially had used a different imitation model on line grid. This model uses preferential attachment network as a metaphor for social networks influencing adoption. The preferential network can be adjusted in the model to be created based on both nodes preferred due to higher rank as well as a mild preference for nodes of a like group.

WWHW is an agent-based model designed to allow the exploration of the emergence, resilience and evolution of cooperative behaviours in hunter-fisher-gatherer societies.

Agent based approach to the class of the Integrated Assessment Models. An agent-based model (ABM) that focuses on the energy sector and climate relevant facts in a detailed way while being complemented with consumer goods, labour and capital markets to a minimal necessary extent.

This model is an extension of the Netlogo Wolf-sheep predation model by U.Wilensky (1997). This extended model studies several different behavioural mechanisms that wolves and sheep could adopt in order to enhance their survivability, and their overall impact on global equilibrium of the system.

SERDUX-MARCIM simulates the propagation of a cyberattack over the computational network of an organization in the maritime sector, at the strategic level of decision-making. It is the instantiation of ABM-MARCIM, the agent-based model of the MARCIM framework for the modeling and simulation of maritime cyberdefense.

Every computational asset of the target organization – servers, endpoints, routers, gateways, vessel systems, radars – is an agent that occupies one of six states at each time step: Susceptible, Exposed, Resistant, Degraded, Unavailable or Destroyed, the initials of which give the model its name. The states Degraded, Unavailable and Destroyed are associated with the D5 cyberattack effects (disrupt, degrade, deny, destroy, deceive) as a function of the degree and the duration of the attack. Thirteen transitions between states are admissible.

Unlike a conventional agent-based model, the local update function is not an individual behavioral rule. It is a system of six ordinary differential equations with eight time-dependent transition rates – propagation, cyberattack (degraded), cyberattack (unavailable), cyberattack (destroyed), recovery, sanitation, loss of resistance, and unavailability by other causes. The values of those rates derive from the capabilities of the target organization, the capabilities of the attacker, and the degree and duration of the cyberattack, computed through a cyber risk approach aligned with the OWASP Risk Rating Methodology, the ISACA categorization of security controls and the IMO Guidelines on Maritime Cyber Risk Management.

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