Combined on-line and off-line trust mechanism for agent computing

In this paper, we propose an efficient mechanism dealing with trust assessment for agent societies, aiming to accurately assess the trustworthiness of the collaborating agents. In the proposed model, we formulate on-line assessment process, which applies a number of measurements affecting the evaluator agent's estimated value regarding to the evaluated agent's trust. We then represent the off-line trust assessment, which compares and adjusts the involved features with the actual performance of the evaluated agent. The off-line process updates the belief set of the evaluator agents in the sense that it adapts the agents with respect to the changes in the network. In this paper, the proposed framework is described, a theoretical analysis of its assessment and its implementation along with simulations comparison with other models are provided. We also show how our model is more efficient than the existing models, particularly in very dynamic environments.