CORE, a trust model is proposed trying to solve agent coalition formation problem. The model characterizes an agent's trust from two aspects of competence and reputation. In the paper, the Euclidean distance formula of vector space on competence field is used to measure the extent which an agent fitting for a particular task, and the membership function is used to characterize an agent's reputation. At the begin of the task, appropriate agents are selected to form a coalition according to their trust value; in the process of the task, the agent's competence gains and reputation updates; after completing the task, the model can renovate every agent's trust according to their behavior during the coalition, which is viewed as an evidence for next task. Finally, the model is carried out by programming on the NetLogo platform.
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