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 combines the two elements of disorganization and motivation to explore their impact on teams. Effects of disorganization on team task performance (problem solving)

This is a model of the occurrence of disorganization and its impact on individual goal setting and problem-solving. This model therefore, explores the effects of disorganization on goal achievement.

This model builds on inquisitiveness as a key individual disposition to expand the bounds of their rationality. It represents a system where teams are formed around problems and inquisitive agents integrate competencies to find ‘emergent’ solutions.

Continuing on from the Adder model, this adaptation explores how rationality, learning and uncertainty influence the exploration of complex landscapes representing technological evolution.

I extend Lazer’s model by adding agent’s two kinds of imitation strategies: selective imitation and structurally equivalent imitation. I examined the effect of interaction of network with agent behavi