Biological agents demonstrate a remarkable proficiency in calibrating appropriate scales of
planning and evaluation when interacting with their environments. It follows logically that …

The article addresses the accelerating human–machine interaction using the large
language model (LLM). It goes beyond the traditional logical paradigms of explainable …

Understanding adaptive human driving behavior, in particular how drivers manage
uncertainty, is of key importance for developing simulated human driver models that can be …

Given the rapid advancement of artificial intelligence, understanding the foundations of
intelligent behaviour is increasingly important. Active inference, regarded as a general …

In a recent computational framework called active inference, discrete models can be linked
to their continuous counterparts to perform decision-making in changing environments. From …

Human learning essentially involves embodied interactions with the material world. But our
worlds now include increasing numbers of powerful and (apparently) disembodied …

Sensational claims portray AI as an entity beyond human control. We argue that while AI
may exhibit characteristics that appear" beyond control," this does not necessarily arise from …

The aim of this short paper is to present the connection between the cognitive framework of
predictive processing and active inference and existing implementation in AI tools, in order …

The Secure Ontologies for the Internet of Things (SOfIoTS) project seeks to advance our
understanding of the current state-of-the-art in respect of IoT security ontologies. It also aims …