# An Adaptive Dempster-Shafer Theory of Evidence Based Trust Model in Multiagent Systems
## 2 Related Work
In most circumstances, credibility can be interpreted as a weight indicating how much the agent could be reliable [12]. It is updated according to the provided information and the interactive feedback [12, 24, 28, 29]. However, in the literature [12, 28], the credibility of the third party agents decreases gradually; that is to say, the truster will no longer believe the agents with sufficient interactions. In the literature [29], the Dempster-Shafer theory of evidence is used to reach trust. However, the credibility of the third-party agents increases if the feedback is a success, and the other way around. In dynamic MASs, false information might also be reliable, and it can be caused by changing performance. Thus, improving agents' credibility through current interactions can be questionable and not enough. Certainty is \"a measure of confidence that an agent may place in the trust information\" [15]. Measuring certainty can filter out reliable information efficiently [33]. As previously stated, trust always involves uncertainty caused by the lack of certainty, a lack of right and complete information, or randomness [34]. Thus, the information that comes from a different degree of certainty may affect the confidence of that agent. For instance, agent A always trusts agent B, yet agent B is uncertain about its information towards some event. Thus, agent A would hesitate at the collected information from agent B. In the literature [31], the trust model uses fuzzy sets and assigns certainty to each evaluation. In [15], the model analyzed certainty to capture confidence. Most trust models believe that certainty and trust are independent. However, we consider trust as the rate of successful interaction. Thus, uncertainty comes from the conflict between successful and failed interactions, and certainty should depend on evidence. In summary, the influential factors and their explanations for trust estimation in MASs are listed in Table 1. As we can see, from our perspective, we value uncertainty, evidence consistency, witness' credibility, and certainty and the motivation for a witness, and they are influential factors for trust estimation in MASs. In what follows, we will display some of the recent trust estimation models that are related to confidence estimation. FIRE is an integrated trust and reputation model for open MASs according to interaction trust (IT), role-based trust (RT), witness trust (WT), and certified trust (CT) [35]. It is direct trust calculated by direct experience; RT, WT, and CT are about witness experience. FIRE presents good performance. However, the model does not stress uncertainty and assumes that all agents provide accurate information. In addition, many static parameters must be used in the model, which limits its application [24, 36]. SecuredTrust is a dynamic trust computation model in MASs [32]. The model addresses many factors, including differences and similarities. However, feedback credibility generated from similarity is used to capture the degree of accuracy of the feedback information, which is the same as consistency. However, certainty and personal credibility are not well stressed. At the same time, an incentive mechanism should be used to encourage agents to be reliable. The actor-critic model selects reliable witnesses by reinforcement learning [37]. It dynamically selects credible witnesses as well as the parameters associated with the direct and indirect trust evidence based on interactive feedback. Nevertheless, when only one known witness is available for the indirect reputation, bootstrapping errors occur [38]. What is more, capturing uncertainty in a perfect trust estimation model in a dynamic system is necessary. By analyzing uncertainty, we can obtain a degree of certainty and filter out reliable agents efficiently. An adaptive trust model for mobile agent systems is established. The model combines direct trust and indirect reputation and also assesses the credibility of witnesses. Moreover, the model considers that uncertainty when generating direct trust is reasonable.