相关论文: Clustering Trust Dynamics in a Human-Robot Sequent…

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).…

Trust is central to human social interactions, manifesting in actions that make one vulnerable to another. We argue that trust will thus depend on the decision-making processes that arise in neural systems. Building on advances in the…

We present a substantial extension of our Human-Aware Task Planning framework, tailored for scenarios with intermittent shared execution experiences and significant belief divergence between humans and robots, particularly due to the…

Trust is crucial for ensuring the safety, security, and widespread adoption of automated vehicles (AVs), and if trust is lacking, drivers and the public may not be willing to use them. This research seeks to investigate trust profiles in…

Large language models (LLMs) increasingly support heterogeneous tasks within a single interface, requiring users to form, update, and act upon beliefs about one system across domains with different reliability profiles. Understanding how…

Humans often assume that robots are rational. We believe robots take optimal actions given their objective; hence, when we are uncertain about what the robot's objective is, we interpret the robot's actions as optimal with respect to our…

Consensus between humans and robots is crucial as robotic agents become more prevalent and deeply integrated into our daily lives. This integration presents both unprecedented opportunities and notable challenges for effective…

We present a framework for learning human user models from joint-action demonstrations that enables the robot to compute a robust policy for a collaborative task with a human. The learning takes place completely automatically, without any…

Trust in human-robot interactions (HRI) is measured in two main ways: through subjective questionnaires and through behavioral tasks. To optimize measurements of trust through questionnaires, the field of HRI faces two challenges: the…

Scientists and philosophers have debated whether humans can trust advanced artificial intelligence (AI) agents to respect humanity's best interests. Yet what about the reverse? Will advanced AI agents trust humans? Gauging an AI agent's…

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…

Trust has been shown to be a key factor in effective human-robot collaboration. In the context of assistive robotics, the effect of trust factors on human experience is further pronounced. Personalization of assistive robots is an…

This paper presents a human-robot trust integrated task allocation and motion planning framework for multi-robot systems (MRS) in performing a set of tasks concurrently. A set of task specifications in parallel are conjuncted with MRS to…

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…

Uncertainty of decisions in safety-critical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decision models. The use of decision tree (DT) models assists…

Driven by ongoing improvements in machine learning, chatbots have increasingly grown from experimental interface prototypes to reliable and robust tools for process automation. Building on these advances, companies have identified various…

The actions of intelligent agents, such as chatbots, recommender systems, and virtual assistants are typically not fully transparent to the user. Consequently, using such an agent involves the user exposing themselves to the risk that the…

Theory of Mind (ToM) is a fundamental cognitive architecture that endows humans with the ability to attribute mental states to others. Humans infer the desires, beliefs, and intentions of others by observing their behavior and, in turn,…

Trust in robots has been gathering attention from multiple directions, as it has special relevance in the theoretical descriptions of human-robot interactions. It is essential for reaching high acceptance and usage rates of robotic…

Joint human-AI inference holds immense potential to improve outcomes in human-supervised robot missions. Current day missions are generally in the AI-assisted setting, where the human operator makes the final inference based on the AI…