Related papers: A Probabilistic Approach for Maintaining Trust Bas…
An agent's assessment of its trust in another agent is commonly taken to be a measure of the reliability/predictability of the latter's actions. It is based on the trustor's past observations of the behaviour of the trustee and requires no…
We study the problem of an agent continuously faced with the decision of placing or not placing trust in an institution. The agent makes use of Bayesian learning in order to estimate the institution's true trustworthiness and makes the…
A model for the joint evolution of opinions and how much the agents trust each other is presented. The model is built using the framework of the Continuous Opinions and Discrete Actions (CODA) model. Instead of a fixed probability that the…
One of the risks involved in multi agent community is in the identification of trustworthy agent partners for transaction. In this paper we aim to describe a trust model for measuring trust in the interacting agents. The trust metric model…
Trust evaluation is an important topic in both research and applications in sociable environments. This paper presents a model for trust evaluation between agents by the combination of direct trust, indirect trust through neighbouring links…
In this paper, we present a model of a trust-based recommendation system on a social network. The idea of the model is that agents use their social network to reach information and their trust relationships to filter it. We investigate how…
We present a model for studying communities of epistemically interacting agents who update their belief states by averaging (in a specified way) the belief states of other agents in the community. The agents in our model have a rich belief…
We present a simple dynamical model for describing trading interactions between agents in a social network by considering only two dynamical variables, namely money and goods or services, that are assumed conserved over the whole time span…
Handling trust is one of the core requirements for facilitating effective interaction between the human and the AI agent. Thus, any decision-making framework designed to work with humans must possess the ability to estimate and leverage…
Agents can achieve effective interaction with previously unknown other agents by maintaining beliefs over a set of hypothetical behaviours, or types, that these agents may have. A current limitation in this method is that it does not…
This work proposes a framework that incorporates trust in an ad hoc teamwork scenario with human-agent teams, where an agent must collaborate with a human to perform a task. During the task, the agent must infer, through interactions and…
In many large scale distributed systems and on the web, agents need to interact with other unknown agents to carry out some tasks or transactions. The ability to reason about and assess the potential risks in carrying out such transactions…
Classic evaluation methods of believable agents are time-consuming because they involve many human to judge agents. They are well suited to validate work on new believable behaviours models. However, during the implementation, numerous…
We consider a multi-agent system where agents aim to achieve a consensus despite interactions with malicious agents that communicate misleading information. Physical channels supporting communication in cyberphysical systems offer…
As AI technology develops, trust in AI agents is becoming more important for more AI applications in human society. Possible ways to improve the trust relationship include empathy, success-failure series, and capability (performance).…
The paper begins by exploring the rationality of ethical trust as a foundational concept. This involves distinguishing between trust and trustworthiness and delving into scenarios where trust is both rational and moral. It lays the…
How do people build up trust with artificial agents? Here, we study a key component of interpersonal trust: people's ability to evaluate the competence of another agent across repeated interactions. Prior work has largely focused on…
Trust is a crucial component in collaborative multiagent systems (MAS) involving humans and autonomous AI agents. Rather than assuming trust based on past system behaviours, it is important to formally verify trust by modelling the current…
This paper is aimed at the stipulations which arise in the traditional online auctions as a result of various anomalies in the reputation and trust calculation mechanism. We try to improve the scalability and efficiency of the online…
Traditionally, an agent's beliefs would come from what the agent can see, hear, or sense. In the modern world, beliefs are often based on the data available to the agents. In this work, we investigate a dynamic logic of such beliefs that…