Human-AI collaborative innovation relies on effective and clearly defined role allocation, yet empirical research in this area remains limited. To address this gap, we construct a cognitive taxonomy trust in AI framework to describe and explain its i...
BACKGROUND: This study intends to investigate the relationship between artificial intelligence and teachers' collaboration in educational research in response to the growing use of technologies and the current status of the field.
In a series of four online experimental studies (total Nā=ā3,562), we investigated the performance augmentation effect and psychological deprivation effect of human-generative AI (GenAI) collaboration in professional settings. Our findings consistent...
Recommender Systems (RS) aim to predict users' latent interests in items by learning embeddings from user-item graphs. Graph Neural Networks (GNNs) have significantly advanced RS by enabling the embedding of graph-structured data. However, relying so...
A canonical social dilemma arises when resources are allocated to people, who can either reciprocate with interest or keep the proceeds. The right resource allocation mechanisms can encourage levels of reciprocation that sustain the commons. Here, in...
Neural networks : the official journal of the International Neural Network Society
Feb 11, 2025
Navigating multi-agent reinforcement learning (MARL) environments with sparse rewards is notoriously difficult, particularly in suboptimal settings where exploration can be prematurely halted. To tackle these challenges, we introduce Hierarchical Sym...
In the context of the technological revolution and the digital intelligence era, the contradiction between the rising incidence of diseases and the uneven distribution of quality medical resources is highlighted, and the diagnosis and prevention of d...
Neural networks : the official journal of the International Neural Network Society
Dec 29, 2024
In multi-agent cooperative tasks, the presence of heterogeneous agents is familiar. Compared to cooperation among homogeneous agents, collaboration requires considering the best-suited sub-tasks for each agent. However, the operation of multi-agent s...
Neural networks : the official journal of the International Neural Network Society
Dec 14, 2024
Distributional Reinforcement Learning (RL) extends beyond estimating the expected value of future returns by modeling its entire distribution, offering greater expressiveness and capturing deeper insights of the value function. To leverage this advan...
The development of Industry 4.0 has resulted in tremendous transformations in the manufacturing sector to supplement the human workforce through collaboration with robots. This emphasis on a human-centered approach is a vital aspect in promoting resi...
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