A series of studies show the applicability of the NK model in the crowdsourcing research, but it also exposes a problem that the application of the NK model is not tightly integrated with crowdsourcing process, which leads to lack of a basic crowdsourcing simulation model. Accordingly, by introducing interaction relationship among task decisions to define three tasks of different structure: local task, small-world task and random task, and introducing bounded rationality and its two dimensions are taken into account: bounded rationality level that used to distinguish industry types and bounded rationality bias that used to differentiate professional users and ordinary users, an agent-based model that simulates the problem-solving process of tournament-based crowdsourcing is constructed by combining the NK fitness landscapes and the crowdsourcing framework of “Task-Crowd-Process-Evaluation”.

The model formalizes a situation where agents embedded in different types of networks (random, small world and scale free networks) interact with their neighbors and express an opinion that is the result of different mechanisms: a coherence mechanism, in which agents try to stick to their previously expressed opinions; an assessment mechanism, in which agents consider available external information on the topic; and a social influence mechanism, in which agents tend to approach their neighbor’s opinions.

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.

We used a computer simulation to measure how well different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment.

This model simulates how collective self-organisation among individuals that manage irrigation resource collectively.

This adaptation of the Relative Agreement model of opinion dynamics (Deffuant et al. 2002) extends the Meadows and Cliff (2012) implementation of this model in a manner that explores the effect of the network structure among the agents.

Agents co-operate or defect towards other agents in a prisoner’s dilemma, with strategy choice depending on whether agents share tags or are kin in different social structures.

This model simulates diffusion curves and it allows to test how social influence, network structure and consumer heterogeneity affect their spreads and their speeds.

NetLogo implementation of Linear Threshold model of influence propagation.

The model is an experimental ground to study the impact of network structure on diffusion. It allows to construct a social network that already has some measurable level of homophily, and simulate a diffusion process over this social network.