Using nodes from the 2002 General Social Survey sample, the code establishes a network of ties with a given homophily bias, and simulates Internet adoption rates in that network under three conditions: (i) no network externalities, (ii) general network externalities, where an individual’s reservation price is a function of the overall adoption rate in the network, (iii) specific network externalities, where reservation price is a function of the adoption rate in individual’s personal […]

The teamCognition model investigates team decision processes by using an agent-based model to conceptualize team decisions as an emergent property. It uses a mixed-method research design with a laboratory experiment providing qualitative and quantitative input for the model’s construction, as well as data for an output validation of the model. The agent-based model is used as a computational testbed to contrast several processes of team decision making, representing potential, simplified mechanisms of how a team decision emerges. The increasing overall fit of the simulation and empirical results indicates that the modeled decision processes can at least partly explain the observed team decisions.

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.

This model represents informal information transmission networks among medieval Genoese investors used to inform each other about cheating merchants they employed as part of long-distance trade operations.

This is the R code of the mathematical model used for verification. This code corresponds to equations 1-9, 15-53, 58-62, 69-70, and 72-75 given in the paper “A Mathematical Model of The Beer Game”.

This MAS simulates the traffic of Barcelona Eixample. Uses a centralized AI system in order to control the traffic lights. Car agents are reactive and have no awareness of the intelligence of the system. They (try to) avoid collisions.

This Agent-Based model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts.

This model is programmed in Python 3.6. We model how different consensus protocols and trade network topologies affect the performance of a blockchain system. The model consists of multiple trader and miner agents (Trader.py and Tx.py), and one system agent (System.py). We investigated three consensus protocols, namely proof-of-work (PoW), proof-of-stake (PoS), and delegated proof-of-stake (DPoS). We also examined three common trade network topologies: random, small-world, and scale-free. To reproduce our results, you may need to create some databases using, e.g., MySQL; or read and write some CSV files as model configurations.

This simulation model is associated with the journal paper “A First Approach on Modelling Staff Proactiveness in Retail Simulation Models” to appear in the Journal of Artificial Societies and Social Simulation 14 (2) 2. The authors are Peer-Olaf Siebers ([email protected]) and Uwe Aickelin ([email protected]).

An empirically validated agent-based model of circular migration