The utility of our actions frequently depends upon the beliefs and behavior of other agents.
Thankfully, through experience, we learn norms and conventions that provide stable …

This paper introduces DAC-HRC, a novel cognitive architecture designed to optimize human-
robot collaboration (HRC) in industrial settings, particularly within the context of Industry 4.0 …

Deep reinforcement learning algorithms are known for their sample inefficiency, requiring
extensive episodes to reach optimal performance. Episodic reinforcement learning …

A major challenge in cognitive science and AI has been to understand how intelligent
autonomous agents might acquire and predict the behavioral and mental states of other …

Humans routinely form groups to achieve goals that no individual can accomplish alone.
Group coordination often brings to mind synchrony and alignment, where all individuals do …

In this perspective article, we show that a morphospace, based on information-theoretic
measures, can be a useful construct for comparing biological agents with artificial …

Living systems ensure their fitness by self-regulating. The optimal matching of their behavior
to the opportunities and demands of the ever-changing natural environment is crucial for …

A major challenge in cognitive science and AI has been to understand how autonomous
agents might acquire and predict behavioral and mental states of other agents in the course …

Au cours des dernières années, on assiste à la montée en puissance d'un discours en
faveur de l'intégration des fonctionnalités de l'intelligence artificielle aux pratiques de …

Social learning, a cornerstone of cultural evolution, enables individuals to acquire
knowledge by observing and imitating others. At the heart of its efficacy lies episodic …